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PCA demonstration.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# PCA demonstration\n",
"### July 28, 2015"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### When can we use PCA? What does it do?\n",
"\n",
"- PCA is useful for identifying correlations between predictor features. We can discover latent features from the output components from performing principal component analysis.\n",
"- One potential negative of PCA is that components may be harder to interpret than the original features when models are fit on them. But on high-dimensionality datasets, this can actually provide meaning to data that may not have an obvious prior grouping.\n",
"- PCA can be used to drastically reduce the size of the feature space. This can make PCA good as a pre-processing step, especially when we have a lot of features but our data would not be enough to \"fill\" the space taken as given.\n",
"- Similarly, PCA is good for noise reduction, to try and improve our algorithms' abilities to fit to the underlying signal in the data.\n",
"- A reduced feature space can make it easier to visualize data that has a high dimensionality."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"from sklearn import decomposition, preprocessing\n",
"%matplotlib inline\n",
"\n",
"# for interactive plotting with hover\n",
"import mpld3\n",
"from mpld3 import plugins"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>completion_male</th>\n",
" <th>completion_female</th>\n",
" <th>income_per_person</th>\n",
" <th>employment</th>\n",
" <th>life_expectancy</th>\n",
" </tr>\n",
" <tr>\n",
" <th>country</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Afghanistan</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1193.282161</td>\n",
" <td>56.000000</td>\n",
" <td>53.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Albania</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>8090.423280</td>\n",
" <td>51.400002</td>\n",
" <td>74.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Algeria</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>12088.087622</td>\n",
" <td>50.000000</td>\n",
" <td>74.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Angola</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>5303.703307</td>\n",
" <td>75.500000</td>\n",
" <td>56.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Argentina</th>\n",
" <td>97.91143</td>\n",
" <td>102.10666</td>\n",
" <td>12912.711243</td>\n",
" <td>58.400002</td>\n",
" <td>75.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" completion_male completion_female income_per_person \\\n",
"country \n",
"Afghanistan NaN NaN 1193.282161 \n",
"Albania NaN NaN 8090.423280 \n",
"Algeria NaN NaN 12088.087622 \n",
"Angola NaN NaN 5303.703307 \n",
"Argentina 97.91143 102.10666 12912.711243 \n",
"\n",
" employment life_expectancy \n",
"country \n",
"Afghanistan 56.000000 53.2 \n",
"Albania 51.400002 74.5 \n",
"Algeria 50.000000 74.8 \n",
"Angola 75.500000 56.9 \n",
"Argentina 58.400002 75.5 "
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# data from www.gapminder.org/data/\n",
"filenames = [\"completion_male.csv\", \"completion_female.csv\", \"income_per_person.csv\",\n",
" \"employment_over_15.csv\", \"life_expectancy.csv\"]\n",
"gapminder_data = []\n",
"for name in filenames: gapminder_data.append(pd.read_csv(name, index_col=0))\n",
"# create a dataframe with multiple features per country\n",
"df = pd.concat(gapminder_data, join=\"inner\", axis=1)\n",
"df.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>completion_male</th>\n",
" <th>completion_female</th>\n",
" <th>income_per_person</th>\n",
" <th>employment</th>\n",
" <th>life_expectancy</th>\n",
" </tr>\n",
" <tr>\n",
" <th>country</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Argentina</th>\n",
" <td>97.91143</td>\n",
" <td>102.10666</td>\n",
" <td>9.465967</td>\n",
" <td>58.400002</td>\n",
" <td>75.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Armenia</th>\n",
" <td>91.53127</td>\n",
" <td>94.58897</td>\n",
" <td>8.749288</td>\n",
" <td>39.400002</td>\n",
" <td>72.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Austria</th>\n",
" <td>100.63802</td>\n",
" <td>101.12819</td>\n",
" <td>10.656714</td>\n",
" <td>57.099998</td>\n",
" <td>80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Azerbaijan</th>\n",
" <td>91.68856</td>\n",
" <td>90.66259</td>\n",
" <td>9.264091</td>\n",
" <td>59.299999</td>\n",
" <td>69.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bahamas</th>\n",
" <td>99.76959</td>\n",
" <td>96.84352</td>\n",
" <td>10.133238</td>\n",
" <td>66.900002</td>\n",
" <td>72.1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" completion_male completion_female income_per_person employment \\\n",
"country \n",
"Argentina 97.91143 102.10666 9.465967 58.400002 \n",
"Armenia 91.53127 94.58897 8.749288 39.400002 \n",
"Austria 100.63802 101.12819 10.656714 57.099998 \n",
"Azerbaijan 91.68856 90.66259 9.264091 59.299999 \n",
"Bahamas 99.76959 96.84352 10.133238 66.900002 \n",
"\n",
" life_expectancy \n",
"country \n",
"Argentina 75.5 \n",
"Armenia 72.2 \n",
"Austria 80.0 \n",
"Azerbaijan 69.9 \n",
"Bahamas 72.1 "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# keep only countries for which we have a complete set of features\n",
"# (no missing data in any of the columns)\n",
"df.dropna(axis=0, how=\"any\", inplace=True)\n",
"\n",
"# take the log of income_per_person \n",
"# - this variable follows approximately a log-normal distribution\n",
"df.income_per_person = np.log(df.income_per_person)\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(105, 5)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Perform PCA"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[-1.03975554 0.23058621]\n",
" [-0.67166986 -1.75975392]\n",
" [-1.80668446 0.46156378]\n",
" [-0.21292093 0.13139593]\n",
" [-0.85548708 1.05467569]\n",
" [-0.56685139 1.01592655]\n",
" [-0.51592526 -0.39585543]\n",
" [-1.38476499 -0.376583 ]\n",
" [-0.48263095 -0.06380433]\n",
" [ 1.20094548 -0.04428261]]\n"
]
}
],
"source": [
"pca = decomposition.PCA(n_components=2)\n",
"\n",
"# we need to scale data with mean = 0 and stdev = 1\n",
"scaled_data = preprocessing.scale(df)\n",
"\n",
"pca.fit(scaled_data)\n",
"transformed = pca.transform(scaled_data)\n",
"# let's take a look at the first ten rows of the transformed data\n",
"print transformed[:10, :]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Components"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[-0.50283735 -0.50886538 -0.46864391 0.22640338 -0.46618131]\n",
" [-0.01732469 -0.01884488 0.23200303 0.93671022 0.26094689]]\n"
]
}
],
"source": [
"print pca.components_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we perform PCA on the unscaled data, the third feature (income_per_person) receives very little weight because its variance is much smaller than that of the rest of the features. "
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[-0.61657745 -0.74355248 -0.02973757 0.12911842 -0.22227476]\n",
" [-0.08065149 -0.07316974 -0.00860175 -0.98849972 -0.1045746 ]]\n"
]
}
],
"source": [
"pca_unscaled = decomposition.PCA(n_components=2)\n",
"pca_unscaled.fit(df)\n",
"print pca_unscaled.components_"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Components are orthogonal to each other (dot product = 0)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"6.9388939039072284e-17"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.dot(pca.components_[0], pca.components_[1])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Components are normaled to have length 1. "
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 1., 1.])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(pca.components_.T**2).sum(axis=0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Variance explained by the first two components. "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[ 0.66304229 0.18088559]\n"
]
}
],
"source": [
"print pca.explained_variance_ratio_"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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p8WGORKRlCXsiLSLSmuTl5fHlT1n02jk13KGIhMTKNRtYazMB6GsyGNa/R1jj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\nU6O1AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x109d8de50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12, 8))\n",
"sns.regplot(transformed[:, 0], transformed[:, 1], fit_reg=False)\n",
"feature_vectors = pca.components_.T\n",
"arrow_size, text_pos = 2.0, 2.5\n",
"for i, v in enumerate(feature_vectors):\n",
" plt.arrow(0, 0, arrow_size*v[0], arrow_size*v[1], \n",
" head_width=0.05, head_length=0.1)\n",
" plt.text(v[0]*text_pos, v[1]*text_pos, df.columns[i], color='r', \n",
" ha='center', va='center', fontsize=16)\n",
"plt.xlabel(\"PC1\", fontsize=14)\n",
"plt.ylabel(\"PC2\", fontsize=14)\n",
"plt.title(\"PC plane with original feature projections.\", fontsize=18)\n",
"plt.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Difference in completion rates"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Let's take a look at the difference in completion rates: (male - female)\n",
"df_diff = df[[\"income_per_person\", \"employment\", \"life_expectancy\"]].copy()\n",
"df_diff[\"diff_completion\"] = df.completion_male - df.completion_female"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[-0.90597675 0.19996421]\n",
" [-0.80896797 -1.78711098]\n",
" [-1.61095973 0.46755818]\n",
" [-0.10251782 0.13118676]\n",
" [-0.34930845 1.08249442]\n",
" [-0.55596969 1.00061914]\n",
" [-0.14798292 -0.36930313]\n",
" [-1.88479375 -0.40214248]\n",
" [ 0.64451439 0.06373349]\n",
" [ 0.43596109 -0.08850266]]\n"
]
}
],
"source": [
"pca_diff = decomposition.PCA(n_components=2)\n",
"scaled_diff = preprocessing.scale(df_diff)\n",
"pca_diff.fit(scaled_diff)\n",
"transformed_diff = pca_diff.transform(scaled_diff)\n",
"print transformed_diff[:10, :]"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[-0.61386772 0.28749627 -0.59301754 0.43456014]\n",
" [ 0.22922163 0.93388978 0.2657174 0.0685682 ]]\n"
]
}
],
"source": [
"print pca_diff.components_"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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JMZUm0oFwsuEdQBzwb8Mw3vP9RdgdlIhIY+LxeHjpldV2hyEi0qAEQo30jcCN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\n73qO2Xc9x93zXxny8xWb4dpukqT+9bcgy5HATGA18MMY420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"text/plain": [
"<matplotlib.figure.Figure at 0x10bcd8d50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(12, 8))\n",
"sns.regplot(transformed_diff[:, 0], transformed_diff[:, 1], fit_reg=False)\n",
"feature_vectors_diff = pca_diff.components_.T\n",
"for i, v in enumerate(feature_vectors_diff):\n",
" plt.arrow(0, 0, arrow_size*v[0], arrow_size*v[1], \n",
" head_width=0.05, head_length=0.1)\n",
" plt.text(v[0]*text_pos, v[1]*text_pos, df_diff.columns[i], color='r', \n",
" ha='center', va='center', fontsize=16)\n",
"plt.xlabel(\"PC1\", fontsize=14)\n",
"plt.ylabel(\"PC2\", fontsize=14)\n",
"plt.title(\"PC plane with original feature projections.\", fontsize=18)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"df_transform = pd.DataFrame(index=df.index, data=transformed_diff, columns=[\"PC1\", \"PC2\"])"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# merge dataframes based on index - \"country\"\n",
"# we now have a dataframe that contains both the components and the original features\n",
"df_transform = df_transform.join(df_diff)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
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false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}, {\"voffset\": 10, \"labels\": [\"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Argentina</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.905977</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.199964</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465967</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.195230</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Armenia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.808968</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.787111</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.749288</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.057700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Austria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.610960</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.467558</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.490170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Azerbaijan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.102518</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.131187</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.264091</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.025970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bahamas</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.349308</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.082494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.133238</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.926070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Barbados</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.555970</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.000619</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.666502</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.923830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belarus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.147983</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.369303</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.377423</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.137070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belgium</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.884794</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.402142</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.615086</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>48.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.924920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belize</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.644514</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.063733</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.031668</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>13.471580</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bhutan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.435961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.088503</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.462929</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>66.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.083280</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bolivia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.633670</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.010190</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.476296</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>70.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.028940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Botswana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.235750</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.548748</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465450</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.489470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Brunei</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.761579</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.117032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.247214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.287260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bulgaria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.802000</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.823956</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.498872</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.148880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Burkina Faso</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.735064</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.480493</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.175434</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.247250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cambodia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.548538</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.469431</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.654714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.917590</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cameroon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.995213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.441022</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.844318</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>55.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>8.575600</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Canada</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.416783</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.987985</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.626688</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.470170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cape Verde</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.410376</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.359021</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.523691</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.997490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Chad</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.224026</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.415487</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.537504</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>19.968190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Colombia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.584800</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.407842</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.173344</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>61.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.843070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Congo, Rep.</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.602893</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.141624</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.515644</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.300003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.049310</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Costa Rica</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.032769</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.245337</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.327070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.189040</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cote d'Ivoire</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.826128</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.309127</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.941214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>21.766570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Croatia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.204178</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.740734</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.948518</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.441510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cuba</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.925369</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.121378</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.665211</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.338830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cyprus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.468203</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.572354</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.361799</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.518550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Denmark</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.353173</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.013338</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.712460</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>63.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.588940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ecuador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.327905</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233973</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.070115</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.297940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Egypt</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.370603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.489578</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.104431</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.662670</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>El Salvador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.321007</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.016458</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.872884</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.456470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Eritrea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.601851</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.087701</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.140908</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.484550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Estonia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.634461</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.014002</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.074280</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.037860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ethiopia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.169331</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.320009</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.678998</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>80.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.905990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Fiji</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.216381</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.337254</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.914158</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.142810</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Finland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.491016</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.387910</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.601156</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.201330</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Gambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.767217</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.667468</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.307449</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.999020</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Georgia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.014366</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.320621</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.536519</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.169760</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Germany</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.683238</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.588125</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.540070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ghana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.424216</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.186134</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.869484</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.343550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Greece</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.547999</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.351868</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.352177</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>49.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.031410</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guatemala</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.618512</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.388133</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.802684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.821130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guinea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.557657</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.618504</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.087835</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.020490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guyana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.482678</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.296600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.466218</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.212650</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Honduras</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.109482</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.292528</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.330057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.312550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hong Kong, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.601864</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.665277</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.679305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>82.124000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.604640</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hungary</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.087386</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.746088</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.054576</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.506110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iceland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.429053</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.106433</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.663720</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>74.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.146030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>India</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.010258</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.549648</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.176560</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.413260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Indonesia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.108280</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.051174</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.822841</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.202970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iran</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.877873</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.786061</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.517515</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.031680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Israel</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.599334</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.178126</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.187703</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.121540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Italy</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.880943</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.573439</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.551021</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.936880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Jordan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.183668</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.631719</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.192079</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.360130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kazakhstan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.059126</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.384705</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.742618</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.182900</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kuwait</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.859974</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.341981</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.530443</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.676570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Latvia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.510889</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.027301</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.900620</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.947920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lebanon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.302329</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.929834</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.386067</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.131060</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lesotho</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.777421</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.279319</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.554775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-26.551050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lithuania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.754651</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.348667</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.866371</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>71.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.384950</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macao, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.701157</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.176092</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.178775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.886000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.264630</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macedonia, FYR</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.065774</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.021046</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.189139</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>34.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.805990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Madagascar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.040250</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.844114</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.245745</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>84.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.262260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Malawi</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.958810</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.137607</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.403049</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>49.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.115830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Maldives</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.488208</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.007300</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.089959</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.891300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mali</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.344790</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.800773</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.349243</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>16.086970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.690246</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.429475</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.909027</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.131300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritius</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.763721</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343402</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.475324</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.102180</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mexico</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.831266</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.359393</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.677542</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.271540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Moldova</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.061792</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.414292</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.152535</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.747480</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mongolia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.420594</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.882199</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.672546</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.243210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Morocco</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.026426</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.993344</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.652641</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.208860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mozambique</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.533961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.960934</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.646684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>77.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.250090</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Namibia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.067077</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.133226</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.958044</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-8.595690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nicaragua</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.384837</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.085906</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.249098</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.316270</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Niger</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.669485</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.479940</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.674577</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>58.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>12.607190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nigeria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.123344</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.997983</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.347697</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.773300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Norway</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.720393</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.203416</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.067251</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.861550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Pakistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.535786</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.885726</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.298761</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>50.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>17.711700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Panama</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.733903</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.231397</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.361851</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.122110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Paraguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.171213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.346077</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.739353</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>72.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.173960</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Peru</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.184845</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.060731</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.996081</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>67.800003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.550440</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Philippines</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.166254</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.103345</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.503630</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-7.342690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Qatar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.385143</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.394124</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.750505</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.853210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Romania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.811206</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.473615</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.679253</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.049250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Senegal</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.485882</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233590</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.639393</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.013130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Slovak Republic</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.952964</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343750</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.977585</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.510610</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Spain</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.616734</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045316</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.431980</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.412720</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sri Lanka</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.375175</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.319358</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.724435</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>54.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.734160</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Suriname</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.574603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.359470</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.470836</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-16.395260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Swaziland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.378559</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.565373</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.621692</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.912150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sweden</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.532682</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.790683</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.047830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Switzerland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.730374</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.239032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.876402</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.662370</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Syria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.616681</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.142604</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.680752</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>44.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.277510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tajikistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.823704</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.949089</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.477146</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.506510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tanzania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.334039</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.155094</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.191813</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.362050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Togo</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.189171</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.076340</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.097305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>24.349910</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Turkey</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.761205</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.085115</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.686151</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>43.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.927800</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ukraine</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.035688</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.514178</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.972057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>67.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.691150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United Arab Emirates</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.389287</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.130024</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.476259</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.332680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United States</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.473912</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.935600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.832812</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.771030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uruguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.866187</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.064056</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.497198</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.448210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uzbekistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.564929</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.393984</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.059925</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.730380</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Venezuela</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.027242</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.327579</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.689949</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.746690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Zambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.526822</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.490990</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.002437</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>48.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.728000</td>\\n </tr>\\n </tbody>\\n</table>\"], \"type\": \"htmltooltip\", \"id\": \"el37474479672272pts\", \"hoffset\": 10}], \"data\": {\"data01\": [[-0.9059767466709602, 0.1999642075296948], [-0.8089679667072682, -1.787110981705207], [-1.6109597326639027, 0.4675581840015952], [-0.10251781544973887, 0.1311867639929912], [-0.3493084496838704, 1.0824944223722484], [-0.555969690028334, 1.000619138771026], [-0.14798291653111562, -0.3693031336161806], [-1.8847937507295367, -0.40214247827618393], [0.6445143911682311, 0.06373349470193701], [0.43596108947192685, -0.08850265669440752], [0.6336702721810815, 1.0101904912985837], [-0.23575046953852663, -1.5487475660901404], [-1.7615791595047134, 1.1170318985889753], [-0.8019995765290763, -0.8239561791585369], [2.7350641255944415, 1.480492771233579], [1.5485378678894755, 1.4694312931656472], 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" }(mpld3);\n",
"}else if(typeof define === \"function\" && define.amd){\n",
" // require.js is available: use it to load d3/mpld3\n",
" require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
" require([\"d3\"], function(d3){\n",
" window.d3 = d3;\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
" \n",
" mpld3.register_plugin(\"htmltooltip\", HtmlTooltipPlugin);\n",
" HtmlTooltipPlugin.prototype = Object.create(mpld3.Plugin.prototype);\n",
" HtmlTooltipPlugin.prototype.constructor = HtmlTooltipPlugin;\n",
" HtmlTooltipPlugin.prototype.requiredProps = [\"id\"];\n",
" HtmlTooltipPlugin.prototype.defaultProps = {labels:null, hoffset:0, voffset:10};\n",
" function HtmlTooltipPlugin(fig, props){\n",
" mpld3.Plugin.call(this, fig, props);\n",
" };\n",
"\n",
" HtmlTooltipPlugin.prototype.draw = function(){\n",
" var obj = mpld3.get_element(this.props.id);\n",
" var labels = this.props.labels;\n",
" var tooltip = d3.select(\"body\").append(\"div\")\n",
" .attr(\"class\", \"mpld3-tooltip\")\n",
" .style(\"position\", \"absolute\")\n",
" .style(\"z-index\", \"10\")\n",
" .style(\"visibility\", \"hidden\");\n",
"\n",
" obj.elements()\n",
" .on(\"mouseover\", function(d, i){\n",
" tooltip.html(labels[i])\n",
" .style(\"visibility\", \"visible\");})\n",
" .on(\"mousemove\", function(d, i){\n",
" tooltip\n",
" .style(\"top\", d3.event.pageY + this.props.voffset + \"px\")\n",
" .style(\"left\",d3.event.pageX + this.props.hoffset + \"px\");\n",
" }.bind(this))\n",
" .on(\"mouseout\", function(d, i){\n",
" tooltip.style(\"visibility\", \"hidden\");});\n",
" };\n",
" \n",
" mpld3.draw_figure(\"fig_el374744577829923413893038\", {\"axes\": [{\"xlim\": [-2.0, 4.0], \"yscale\": \"linear\", \"axesbg\": \"#EAEAF2\", \"texts\": [{\"v_baseline\": \"hanging\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"PC1\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 11.0, \"position\": [0.5, -0.062724014336917586], \"rotation\": -0.0, \"id\": \"el37474466947152\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"PC2\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 11.0, \"position\": [-0.040078965053763432, 0.5], \"rotation\": -90.0, \"id\": \"el37474467073808\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"Interactive projection on PC plane\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 20.0, \"position\": [0.5, 1.0149342891278375], \"rotation\": -0.0, \"id\": \"el37474470896848\"}], \"zoomable\": true, \"images\": [], \"xdomain\": [-2.0, 4.0], \"ylim\": [-3.0, 3.0], \"paths\": [], \"sharey\": [], \"sharex\": [], \"axesbgalpha\": null, \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#FFFFFF\", \"alpha\": 1.0, \"dasharray\": \"10,0\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"bottom\", \"nticks\": 7, \"tickvalues\": null}, {\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#FFFFFF\", \"alpha\": 1.0, \"dasharray\": \"10,0\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"left\", \"nticks\": 7, \"tickvalues\": null}], \"lines\": [], \"markers\": [{\"edgecolor\": \"#000000\", \"facecolor\": \"#0000FF\", \"edgewidth\": 1, \"yindex\": 1, \"coordinates\": \"data\", \"zorder\": 2, \"markerpath\": [[[0.0, 7.5], [1.9890232500000002, 7.5], [3.896849030886401, 6.709752686911813], [5.303300858899107, 5.303300858899107], [6.709752686911813, 3.896849030886401], [7.5, 1.9890232500000002], [7.5, 0.0], [7.5, 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false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}, {\"voffset\": 10, \"labels\": [\"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Argentina</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.905977</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.199964</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465967</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.195230</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Armenia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.808968</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.787111</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.749288</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.057700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Austria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.610960</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.467558</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.490170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Azerbaijan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.102518</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.131187</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.264091</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.025970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bahamas</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.349308</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.082494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.133238</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.926070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Barbados</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.555970</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.000619</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.666502</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.923830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belarus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.147983</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.369303</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.377423</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.137070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belgium</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.884794</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.402142</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.615086</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>48.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.924920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belize</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.644514</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.063733</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.031668</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>13.471580</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bhutan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.435961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.088503</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.462929</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>66.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.083280</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bolivia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.633670</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.010190</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.476296</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>70.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.028940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Botswana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.235750</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.548748</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465450</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.489470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Brunei</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.761579</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.117032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.247214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.287260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bulgaria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.802000</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.823956</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.498872</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.148880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Burkina Faso</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.735064</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.480493</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.175434</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.247250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cambodia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.548538</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.469431</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.654714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.917590</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cameroon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.995213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.441022</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.844318</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>55.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>8.575600</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Canada</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.416783</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.987985</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.626688</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.470170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cape Verde</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.410376</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.359021</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.523691</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.997490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Chad</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.224026</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.415487</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.537504</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>19.968190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Colombia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.584800</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.407842</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.173344</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>61.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.843070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Congo, Rep.</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.602893</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.141624</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.515644</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.300003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.049310</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Costa Rica</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.032769</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.245337</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.327070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.189040</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cote d'Ivoire</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.826128</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.309127</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.941214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>21.766570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Croatia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.204178</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.740734</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.948518</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.441510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cuba</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.925369</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.121378</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.665211</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.338830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cyprus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.468203</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.572354</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.361799</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.518550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Denmark</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.353173</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.013338</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.712460</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>63.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.588940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ecuador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.327905</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233973</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.070115</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.297940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Egypt</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.370603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.489578</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.104431</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.662670</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>El Salvador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.321007</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.016458</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.872884</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.456470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Eritrea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.601851</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.087701</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.140908</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.484550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Estonia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.634461</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.014002</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.074280</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.037860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ethiopia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.169331</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.320009</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.678998</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>80.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.905990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Fiji</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.216381</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.337254</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.914158</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.142810</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Finland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.491016</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.387910</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.601156</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.201330</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Gambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.767217</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.667468</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.307449</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.999020</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Georgia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.014366</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.320621</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.536519</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.169760</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Germany</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.683238</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.588125</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.540070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ghana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.424216</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.186134</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.869484</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.343550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Greece</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.547999</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.351868</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.352177</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>49.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.031410</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guatemala</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.618512</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.388133</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.802684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.821130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guinea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.557657</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.618504</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.087835</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.020490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guyana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.482678</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.296600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.466218</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.212650</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Honduras</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.109482</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.292528</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.330057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.312550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hong Kong, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.601864</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.665277</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.679305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>82.124000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.604640</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hungary</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.087386</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.746088</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.054576</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.506110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iceland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.429053</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.106433</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.663720</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>74.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.146030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>India</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.010258</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.549648</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.176560</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.413260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Indonesia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.108280</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.051174</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.822841</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.202970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iran</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.877873</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.786061</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.517515</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.031680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Israel</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.599334</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.178126</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.187703</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.121540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Italy</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.880943</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.573439</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.551021</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.936880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Jordan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.183668</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.631719</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.192079</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.360130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kazakhstan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.059126</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.384705</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.742618</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.182900</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kuwait</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.859974</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.341981</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.530443</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.676570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Latvia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.510889</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.027301</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.900620</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.947920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lebanon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.302329</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.929834</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.386067</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.131060</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lesotho</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.777421</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.279319</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.554775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-26.551050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lithuania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.754651</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.348667</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.866371</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>71.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.384950</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macao, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.701157</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.176092</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.178775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.886000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.264630</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macedonia, FYR</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.065774</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.021046</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.189139</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>34.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.805990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Madagascar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.040250</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.844114</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.245745</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>84.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.262260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Malawi</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.958810</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.137607</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.403049</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>49.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.115830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Maldives</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.488208</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.007300</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.089959</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.891300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mali</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.344790</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.800773</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.349243</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>16.086970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.690246</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.429475</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.909027</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.131300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritius</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.763721</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343402</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.475324</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.102180</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mexico</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.831266</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.359393</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.677542</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.271540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Moldova</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.061792</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.414292</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.152535</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.747480</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mongolia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.420594</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.882199</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.672546</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.243210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Morocco</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.026426</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.993344</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.652641</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.208860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mozambique</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.533961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.960934</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.646684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>77.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.250090</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Namibia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.067077</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.133226</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.958044</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-8.595690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nicaragua</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.384837</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.085906</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.249098</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.316270</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Niger</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.669485</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.479940</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.674577</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>58.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>12.607190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nigeria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.123344</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.997983</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.347697</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.773300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Norway</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.720393</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.203416</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.067251</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.861550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Pakistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.535786</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.885726</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.298761</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>50.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>17.711700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Panama</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.733903</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.231397</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.361851</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.122110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Paraguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.171213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.346077</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.739353</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>72.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.173960</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Peru</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.184845</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.060731</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.996081</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>67.800003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.550440</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Philippines</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.166254</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.103345</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.503630</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-7.342690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Qatar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.385143</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.394124</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.750505</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.853210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Romania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.811206</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.473615</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.679253</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.049250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Senegal</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.485882</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233590</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.639393</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.013130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Slovak Republic</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.952964</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343750</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.977585</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.510610</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Spain</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.616734</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045316</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.431980</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.412720</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sri Lanka</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.375175</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.319358</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.724435</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>54.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.734160</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Suriname</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.574603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.359470</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.470836</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-16.395260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Swaziland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.378559</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.565373</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.621692</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.912150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sweden</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.532682</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.790683</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.047830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Switzerland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.730374</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.239032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.876402</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.662370</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Syria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.616681</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.142604</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.680752</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>44.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.277510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tajikistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.823704</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.949089</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.477146</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.506510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tanzania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.334039</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.155094</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.191813</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.362050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Togo</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.189171</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.076340</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.097305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>24.349910</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Turkey</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.761205</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.085115</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.686151</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>43.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.927800</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ukraine</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.035688</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.514178</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.972057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>67.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.691150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United Arab Emirates</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.389287</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.130024</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.476259</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.332680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United States</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.473912</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.935600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.832812</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.771030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uruguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.866187</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.064056</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.497198</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.448210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uzbekistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.564929</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.393984</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.059925</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.730380</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Venezuela</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.027242</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.327579</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.689949</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.746690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Zambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.526822</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.490990</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.002437</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>48.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.728000</td>\\n </tr>\\n </tbody>\\n</table>\"], \"type\": \"htmltooltip\", \"id\": \"el37474479672272pts\", \"hoffset\": 10}], \"data\": {\"data01\": [[-0.9059767466709602, 0.1999642075296948], [-0.8089679667072682, -1.787110981705207], [-1.6109597326639027, 0.4675581840015952], [-0.10251781544973887, 0.1311867639929912], [-0.3493084496838704, 1.0824944223722484], [-0.555969690028334, 1.000619138771026], [-0.14798291653111562, -0.3693031336161806], [-1.8847937507295367, -0.40214247827618393], [0.6445143911682311, 0.06373349470193701], [0.43596108947192685, -0.08850265669440752], [0.6336702721810815, 1.0101904912985837], [-0.23575046953852663, -1.5487475660901404], [-1.7615791595047134, 1.1170318985889753], [-0.8019995765290763, -0.8239561791585369], [2.7350641255944415, 1.480492771233579], [1.5485378678894755, 1.4694312931656472], 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" });\n",
" });\n",
"}else{\n",
" // require.js not available: dynamically load d3 & mpld3\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
" mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.2.js\", function(){\n",
" \n",
" mpld3.register_plugin(\"htmltooltip\", HtmlTooltipPlugin);\n",
" HtmlTooltipPlugin.prototype = Object.create(mpld3.Plugin.prototype);\n",
" HtmlTooltipPlugin.prototype.constructor = HtmlTooltipPlugin;\n",
" HtmlTooltipPlugin.prototype.requiredProps = [\"id\"];\n",
" HtmlTooltipPlugin.prototype.defaultProps = {labels:null, hoffset:0, voffset:10};\n",
" function HtmlTooltipPlugin(fig, props){\n",
" mpld3.Plugin.call(this, fig, props);\n",
" };\n",
"\n",
" HtmlTooltipPlugin.prototype.draw = function(){\n",
" var obj = mpld3.get_element(this.props.id);\n",
" var labels = this.props.labels;\n",
" var tooltip = d3.select(\"body\").append(\"div\")\n",
" .attr(\"class\", \"mpld3-tooltip\")\n",
" .style(\"position\", \"absolute\")\n",
" .style(\"z-index\", \"10\")\n",
" .style(\"visibility\", \"hidden\");\n",
"\n",
" obj.elements()\n",
" .on(\"mouseover\", function(d, i){\n",
" tooltip.html(labels[i])\n",
" .style(\"visibility\", \"visible\");})\n",
" .on(\"mousemove\", function(d, i){\n",
" tooltip\n",
" .style(\"top\", d3.event.pageY + this.props.voffset + \"px\")\n",
" .style(\"left\",d3.event.pageX + this.props.hoffset + \"px\");\n",
" }.bind(this))\n",
" .on(\"mouseout\", function(d, i){\n",
" tooltip.style(\"visibility\", \"hidden\");});\n",
" };\n",
" \n",
" mpld3.draw_figure(\"fig_el374744577829923413893038\", {\"axes\": [{\"xlim\": [-2.0, 4.0], \"yscale\": \"linear\", \"axesbg\": \"#EAEAF2\", \"texts\": [{\"v_baseline\": \"hanging\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"PC1\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 11.0, \"position\": [0.5, -0.062724014336917586], \"rotation\": -0.0, \"id\": \"el37474466947152\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"PC2\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 11.0, \"position\": [-0.040078965053763432, 0.5], \"rotation\": -90.0, \"id\": \"el37474467073808\"}, {\"v_baseline\": \"auto\", \"h_anchor\": \"middle\", \"color\": \"#262626\", \"text\": \"Interactive projection on PC plane\", \"coordinates\": \"axes\", \"zorder\": 3, \"alpha\": 1, \"fontsize\": 20.0, \"position\": [0.5, 1.0149342891278375], \"rotation\": -0.0, \"id\": \"el37474470896848\"}], \"zoomable\": true, \"images\": [], \"xdomain\": [-2.0, 4.0], \"ylim\": [-3.0, 3.0], \"paths\": [], \"sharey\": [], \"sharex\": [], \"axesbgalpha\": null, \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#FFFFFF\", \"alpha\": 1.0, \"dasharray\": \"10,0\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"bottom\", \"nticks\": 7, \"tickvalues\": null}, {\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#FFFFFF\", \"alpha\": 1.0, \"dasharray\": \"10,0\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"left\", \"nticks\": 7, \"tickvalues\": null}], \"lines\": [], \"markers\": [{\"edgecolor\": \"#000000\", \"facecolor\": \"#0000FF\", \"edgewidth\": 1, \"yindex\": 1, \"coordinates\": \"data\", \"zorder\": 2, \"markerpath\": [[[0.0, 7.5], [1.9890232500000002, 7.5], [3.896849030886401, 6.709752686911813], [5.303300858899107, 5.303300858899107], [6.709752686911813, 3.896849030886401], [7.5, 1.9890232500000002], [7.5, 0.0], [7.5, -1.9890232500000002], [6.709752686911813, -3.896849030886401], [5.303300858899107, -5.303300858899107], [3.896849030886401, -6.709752686911813], [1.9890232500000002, -7.5], [0.0, -7.5], [-1.9890232500000002, -7.5], [-3.896849030886401, -6.709752686911813], [-5.303300858899107, -5.303300858899107], [-6.709752686911813, -3.896849030886401], [-7.5, -1.9890232500000002], [-7.5, 0.0], [-7.5, 1.9890232500000002], [-6.709752686911813, 3.896849030886401], [-5.303300858899107, 5.303300858899107], [-3.896849030886401, 6.709752686911813], [-1.9890232500000002, 7.5], [0.0, 7.5]], [\"M\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"C\", \"Z\"]], \"alpha\": 0.6, \"xindex\": 0, \"data\": \"data01\", \"id\": \"el37474479672272pts\"}], \"id\": \"el37474467188816\", \"ydomain\": [-3.0, 3.0], \"collections\": [], \"xscale\": \"linear\", \"bbox\": [0.125, 0.125, 0.77500000000000002, 0.77500000000000002]}], \"height\": 480.0, \"width\": 800.0, \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}, {\"voffset\": 10, \"labels\": [\"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Argentina</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.905977</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.199964</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465967</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.195230</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Armenia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.808968</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.787111</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.749288</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.057700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Austria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.610960</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.467558</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.490170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Azerbaijan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.102518</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.131187</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.264091</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.025970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bahamas</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.349308</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.082494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.133238</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.926070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Barbados</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.555970</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.000619</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.666502</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>66.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.923830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belarus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.147983</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.369303</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.377423</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.137070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belgium</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.884794</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.402142</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.615086</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>48.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.924920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Belize</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.644514</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.063733</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.031668</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>13.471580</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bhutan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.435961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.088503</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.462929</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>66.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.083280</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bolivia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.633670</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.010190</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.476296</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>70.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.028940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Botswana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.235750</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.548748</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.465450</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.489470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Brunei</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.761579</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.117032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.247214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.287260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Bulgaria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.802000</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.823956</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.498872</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.148880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Burkina Faso</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.735064</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.480493</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.175434</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.247250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cambodia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.548538</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.469431</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.654714</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.917590</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cameroon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.995213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.441022</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.844318</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>55.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>8.575600</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Canada</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.416783</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.987985</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.626688</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.470170</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cape Verde</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.410376</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.359021</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.523691</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.997490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Chad</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.224026</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.415487</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.537504</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>19.968190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Colombia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.584800</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.407842</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.173344</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>61.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.843070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Congo, Rep.</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.602893</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.141624</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.515644</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.300003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.049310</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Costa Rica</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.032769</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.245337</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.327070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.189040</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cote d'Ivoire</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.826128</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.309127</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.941214</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>21.766570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Croatia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.204178</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.740734</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.948518</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.441510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cuba</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.925369</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.121378</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.665211</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.338830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Cyprus</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.468203</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.572354</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.361799</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.518550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Denmark</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.353173</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.013338</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.712460</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>63.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.588940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ecuador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.327905</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233973</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.070115</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.297940</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Egypt</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.370603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.489578</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.104431</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.662670</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>El Salvador</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.321007</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.016458</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.872884</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.456470</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Eritrea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.601851</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.087701</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.140908</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.484550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Estonia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.634461</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.014002</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.074280</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.037860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ethiopia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.169331</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.320009</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.678998</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>80.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.905990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Fiji</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.216381</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.337254</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.914158</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.142810</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Finland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.491016</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.387910</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.601156</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.201330</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Gambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.767217</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.667468</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.307449</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.999020</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Georgia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.014366</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.320621</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.536519</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.169760</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Germany</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.683238</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045494</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.588125</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.540070</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ghana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.424216</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.186134</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.869484</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>61.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>3.343550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Greece</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.547999</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.351868</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.352177</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>49.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.031410</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guatemala</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.618512</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.388133</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.802684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.821130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guinea</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.557657</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.618504</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.087835</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>81.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.020490</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Guyana</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.482678</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.296600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.466218</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.212650</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Honduras</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.109482</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.292528</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.330057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>57.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.312550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hong Kong, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.601864</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.665277</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.679305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>82.124000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.604640</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Hungary</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.087386</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.746088</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.054576</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.506110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iceland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.429053</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.106433</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.663720</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>74.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.146030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>India</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.010258</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.549648</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.176560</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.413260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Indonesia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.108280</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.051174</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.822841</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.202970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Iran</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.877873</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.786061</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.517515</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.031680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Israel</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.599334</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.178126</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.187703</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.121540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Italy</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.880943</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.573439</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.551021</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.936880</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Jordan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.183668</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.631719</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.192079</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>39.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.360130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kazakhstan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.059126</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.384705</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.742618</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>65.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.182900</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Kuwait</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.859974</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.341981</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.530443</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.676570</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Latvia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.510889</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.027301</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.900620</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>70.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.947920</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lebanon</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.302329</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.929834</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.386067</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-4.131060</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lesotho</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.777421</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.279319</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.554775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-26.551050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Lithuania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.754651</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.348667</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.866371</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>71.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.384950</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macao, China</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.701157</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.176092</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.178775</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>78.886000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.264630</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Macedonia, FYR</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.065774</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.021046</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.189139</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>34.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.805990</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Madagascar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.040250</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.844114</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.245745</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>84.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.262260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Malawi</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.958810</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.137607</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.403049</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>71.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>49.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.115830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Maldives</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.488208</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.007300</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.089959</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>55.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.891300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mali</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.344790</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.800773</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.349243</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>16.086970</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.690246</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.429475</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.909027</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>47.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.131300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mauritius</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.763721</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343402</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.475324</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.102180</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mexico</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.831266</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.359393</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.677542</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.271540</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Moldova</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.061792</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.414292</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.152535</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.747480</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mongolia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.420594</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.882199</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.672546</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>62.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.243210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Morocco</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.026426</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.993344</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.652641</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>46.900002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>72.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>7.208860</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Mozambique</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.533961</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.960934</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.646684</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>77.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>54.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>14.250090</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Namibia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.067077</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-2.133226</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.958044</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>41.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>53.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-8.595690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nicaragua</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.384837</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.085906</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.249098</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-6.316270</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Niger</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.669485</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.479940</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>6.674577</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>58.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>12.607190</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Nigeria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.123344</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.997983</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.347697</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>20.773300</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Norway</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.720393</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.203416</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.067251</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.199997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.861550</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Pakistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.535786</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.885726</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.298761</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>50.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>17.711700</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Panama</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.733903</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.231397</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.361851</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>58.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.200000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.122110</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Paraguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.171213</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.346077</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.739353</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>72.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.173960</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Peru</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.184845</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.060731</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.996081</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>67.800003</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.550440</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Philippines</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.166254</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.103345</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.503630</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-7.342690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Qatar</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.385143</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.394124</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.750505</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>79.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.853210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Romania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.811206</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.473615</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.679253</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>73.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.049250</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Senegal</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.485882</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.233590</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.639393</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>65.400002</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>63.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.013130</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Slovak Republic</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.952964</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.343750</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.977585</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.510610</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Spain</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.616734</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.045316</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.431980</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>52.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.412720</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sri Lanka</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.375175</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.319358</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.724435</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>54.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-0.734160</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Suriname</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.574603</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.359470</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.470836</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>45.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-16.395260</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Swaziland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>1.378559</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.565373</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.621692</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>44.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.912150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Sweden</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.532682</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.790683</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.656070</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.299999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>80.700000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.047830</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Switzerland</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.730374</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.239032</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.876402</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.699997</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>81.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.662370</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Syria</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.616681</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.142604</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.680752</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>44.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>76.100000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.277510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tajikistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.823704</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.949089</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.477146</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>51.200001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>69.000000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>4.506510</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Tanzania</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.334039</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>1.155094</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.191813</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>78.099998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>57.900000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>2.362050</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Togo</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>3.189171</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.076340</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>7.097305</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>64.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>59.400000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>24.349910</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Turkey</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.761205</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-1.085115</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.686151</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>43.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>5.927800</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Ukraine</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.035688</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.514178</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.972057</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>53.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>67.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>0.691150</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United Arab Emirates</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.389287</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>2.130024</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>11.476259</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>75.000000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.600000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-3.332680</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>United States</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.473912</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.935600</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>10.832812</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>62.599998</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>77.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-1.771030</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uruguay</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-0.866187</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.064056</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.497198</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>75.500000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-2.448210</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Uzbekistan</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>0.564929</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.393984</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.059925</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>56.500000</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>68.300000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>1.730380</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Venezuela</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>-1.027242</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>0.327579</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>9.689949</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>59.700001</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>74.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>-5.746690</td>\\n </tr>\\n </tbody>\\n</table>\", \"<table border=\\\"1\\\" class=\\\"dataframe\\\">\\n <thead>\\n <tr style=\\\"text-align: right;\\\">\\n <th></th>\\n <th>Zambia</th>\\n </tr>\\n </thead>\\n <tbody>\\n <tr>\\n <th>PC1</th>\\n <td>2.526822</td>\\n </tr>\\n <tr>\\n <th>PC2</th>\\n <td>-0.490990</td>\\n </tr>\\n <tr>\\n <th>income_per_person</th>\\n <td>8.002437</td>\\n </tr>\\n <tr>\\n <th>employment</th>\\n <td>60.799999</td>\\n </tr>\\n <tr>\\n <th>life_expectancy</th>\\n <td>48.800000</td>\\n </tr>\\n <tr>\\n <th>diff_completion</th>\\n <td>10.728000</td>\\n </tr>\\n </tbody>\\n</table>\"], \"type\": \"htmltooltip\", \"id\": \"el37474479672272pts\", \"hoffset\": 10}], \"data\": {\"data01\": [[-0.9059767466709602, 0.1999642075296948], [-0.8089679667072682, -1.787110981705207], [-1.6109597326639027, 0.4675581840015952], [-0.10251781544973887, 0.1311867639929912], [-0.3493084496838704, 1.0824944223722484], [-0.555969690028334, 1.000619138771026], [-0.14798291653111562, -0.3693031336161806], [-1.8847937507295367, -0.40214247827618393], [0.6445143911682311, 0.06373349470193701], [0.43596108947192685, -0.08850265669440752], [0.6336702721810815, 1.0101904912985837], [-0.23575046953852663, -1.5487475660901404], [-1.7615791595047134, 1.1170318985889753], [-0.8019995765290763, -0.8239561791585369], [2.7350641255944415, 1.480492771233579], [1.5485378678894755, 1.4694312931656472], 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" })\n",
" });\n",
"}\n",
"</script>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Example with modifications from:\n",
"# http://mpld3.github.io/examples/html_tooltips.html\n",
"\n",
"# Define some CSS to control our custom labels\n",
"\n",
"css = \"\"\"\n",
"table\n",
"{\n",
" border-collapse: collapse;\n",
"}\n",
"th\n",
"{\n",
" color: #ffffff;\n",
" background-color: #000000;\n",
"}\n",
"td\n",
"{\n",
" background-color: #cccccc;\n",
"}\n",
"table, th, td\n",
"{\n",
" font-family:Arial, Helvetica, sans-serif;\n",
" border: 1px solid black;\n",
" text-align: right;\n",
"}\n",
"\"\"\"\n",
"\n",
"fig, ax = plt.subplots(figsize=(10, 6))\n",
"\n",
"labels = []\n",
"for i in range(len(df_transform)):\n",
" label = df_transform.ix[[i], :].T\n",
" label.columns = [df_transform.index[i]]\n",
" # .to_html() is unicode; so make leading 'u' go away with str()\n",
" labels.append(str(label.to_html()))\n",
"\n",
"points = ax.plot(df_transform.PC1, df_transform.PC2, 'o', color='b',\n",
" mec='k', ms=15, mew=1, alpha=.6)\n",
"\n",
"\n",
"ax.set_xlabel('PC1')\n",
"ax.set_ylabel('PC2')\n",
"ax.set_title('Interactive projection on PC plane', size=20)\n",
"\n",
"tooltip = plugins.PointHTMLTooltip(points[0], labels,\n",
" voffset=10, hoffset=10, css=css)\n",
"plugins.connect(fig, tooltip)\n",
"\n",
"mpld3.display()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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