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caprenter/drc1.ipynb

Created May 13, 2015 10:02
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drc1.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 111,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"df1_1 = pd.read_excel('data/drc/2-rp.org-sources.xlsx', sheetname='Congomines DRC concession data')\n",
"df1_1['source'] = 'rp.org-sources'\n",
"df1_1['country'] = 'Congo - Kinshasa' # Congo - Kinshasa and Congo - Brazzaville are present in the USGS sheeC)"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"df2 = pd.read_csv('data/minfac.csv', encoding='latin-1')\n",
"df2['source'] = 'usgs'"
]
},
{
"cell_type": "code",
"execution_count": 114,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"\"\\ndf3 = df3.rename(columns={\\n 'concessioncontractor': 'company_name',\\n })\\ndf4 = df4.rename(columns={\\n 'contractor': 'company_name',\\n })\\n\""
]
},
"execution_count": 114,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#for df in [df1_1, df1_2, df3, df4]:\n",
"for df in [df1_1, df2]:\n",
" df.columns = map(str.lower, df.columns)\n",
"#df.rename(columns={\n",
"# 'Country': 'country',\n",
"# })\n",
"\n",
"df1_1 = df1_1.rename(columns={\n",
" #'commodity_type': 'commodity',\n",
" 'statut': 'status',\n",
" #'localisation': 'location' # This is not an exact mapping\n",
" #'province': 'location' # This is not an exact mapping\n",
" })\n",
"'''\n",
"df1_2 = df1_2.rename(columns={\n",
" 'komoditas / commodity?': 'commodity',\n",
" 'tahun': 'year',\n",
" 'nama_perusahaan / company name': 'company_name'\n",
" })\n",
"'''\n",
"df2 = df2.rename(columns={\n",
" 'op_comp': 'company_name',\n",
" 'capacity': 'production_volume', # Not 100% sure these are the same, needs checking\n",
" 'units': 'production_unit', # Not 100% sure these are the same, needs checking\n",
" })\n",
"'''\n",
"df3 = df3.rename(columns={\n",
" 'concessioncontractor': 'company_name',\n",
" })\n",
"df4 = df4.rename(columns={\n",
" 'contractor': 'company_name',\n",
" })\n",
"'''"
]
},
{
"cell_type": "code",
"execution_count": 115,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"#combined_df = pd.concat([df1_1, df1_2, df2, df3, df4])\n",
"combined_df = pd.concat([df1_1, df2,])"
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>source</th>\n",
" <th>rp.org-sources</th>\n",
" <th>usgs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>carres</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cite</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>commodity</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>company_name</th>\n",
" <td>0</td>\n",
" <td>5878</td>\n",
" </tr>\n",
" <tr>\n",
" <th>country</th>\n",
" <td>2510</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dmslat</th>\n",
" <td>0</td>\n",
" <td>5685</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dmslong</th>\n",
" <td>0</td>\n",
" <td>5686</td>\n",
" </tr>\n",
" <tr>\n",
" <th>expiration</th>\n",
" <td>2423</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fac_name</th>\n",
" <td>0</td>\n",
" <td>4854</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fac_type</th>\n",
" <td>0</td>\n",
" <td>6337</td>\n",
" </tr>\n",
" <tr>\n",
" <th>latitude</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>localisation</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>location</th>\n",
" <td>0</td>\n",
" <td>5478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>longitude</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>maininvest</th>\n",
" <td>0</td>\n",
" <td>1551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mm</th>\n",
" <td>0</td>\n",
" <td>1190</td>\n",
" </tr>\n",
" <tr>\n",
" <th>notes</th>\n",
" <td>0</td>\n",
" <td>2239</td>\n",
" </tr>\n",
" <tr>\n",
" <th>octroi</th>\n",
" <td>2423</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>othinvest</th>\n",
" <td>0</td>\n",
" <td>306</td>\n",
" </tr>\n",
" <tr>\n",
" <th>position</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>precision</th>\n",
" <td>0</td>\n",
" <td>4120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>production_unit</th>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>production_volume</th>\n",
" <td>0</td>\n",
" <td>6014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>province</th>\n",
" <td>2504</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>rec_id</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>status</th>\n",
" <td>2510</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>type \\n permis</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>year</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"source rp.org-sources usgs\n",
"carres 2510 0\n",
"cite 0 6478\n",
"commodity 0 6478\n",
"company_name 0 5878\n",
"country 2510 6478\n",
"dmslat 0 5685\n",
"dmslong 0 5686\n",
"expiration 2423 0\n",
"fac_name 0 4854\n",
"fac_type 0 6337\n",
"latitude 0 6478\n",
"localisation 2510 0\n",
"location 0 5478\n",
"longitude 0 6478\n",
"maininvest 0 1551\n",
"mm 0 1190\n",
"notes 0 2239\n",
"octroi 2423 0\n",
"othinvest 0 306\n",
"position 0 6478\n",
"precision 0 4120\n",
"production_unit 0 6144\n",
"production_volume 0 6014\n",
"province 2504 0\n",
"rec_id 0 6478\n",
"status 2510 6478\n",
"type \\n permis 2510 0\n",
"year 0 6478"
]
},
"execution_count": 116,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fields = combined_df.groupby('source').count().transpose()\n",
"fields"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"status 2\n",
"country 2\n",
"year 1\n",
"location 1\n",
"cite 1\n",
"commodity 1\n",
"company_name 1\n",
"dmslat 1\n",
"dmslong 1\n",
"expiration 1\n",
"fac_name 1\n",
"fac_type 1\n",
"latitude 1\n",
"localisation 1\n",
"longitude 1\n",
"type \\n permis 1\n",
"maininvest 1\n",
"mm 1\n",
"notes 1\n",
"octroi 1\n",
"othinvest 1\n",
"position 1\n",
"precision 1\n",
"production_unit 1\n",
"production_volume 1\n",
"province 1\n",
"rec_id 1\n",
"carres 1\n",
"dtype: int64"
]
},
"execution_count": 117,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sources_per_field = fields.apply(lambda x: x>0).sum(axis=1)\n",
"sources_per_field.sort(ascending=False)\n",
"sources_per_field"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>source</th>\n",
" <th>rp.org-sources</th>\n",
" <th>usgs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>carres</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>cite</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>commodity</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>company_name</th>\n",
" <td>0</td>\n",
" <td>5878</td>\n",
" </tr>\n",
" <tr>\n",
" <th>country</th>\n",
" <td>2510</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dmslat</th>\n",
" <td>0</td>\n",
" <td>5685</td>\n",
" </tr>\n",
" <tr>\n",
" <th>dmslong</th>\n",
" <td>0</td>\n",
" <td>5686</td>\n",
" </tr>\n",
" <tr>\n",
" <th>expiration</th>\n",
" <td>2423</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fac_name</th>\n",
" <td>0</td>\n",
" <td>4854</td>\n",
" </tr>\n",
" <tr>\n",
" <th>fac_type</th>\n",
" <td>0</td>\n",
" <td>6337</td>\n",
" </tr>\n",
" <tr>\n",
" <th>latitude</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>localisation</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>location</th>\n",
" <td>0</td>\n",
" <td>5478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>longitude</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>maininvest</th>\n",
" <td>0</td>\n",
" <td>1551</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mm</th>\n",
" <td>0</td>\n",
" <td>1190</td>\n",
" </tr>\n",
" <tr>\n",
" <th>notes</th>\n",
" <td>0</td>\n",
" <td>2239</td>\n",
" </tr>\n",
" <tr>\n",
" <th>octroi</th>\n",
" <td>2423</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>othinvest</th>\n",
" <td>0</td>\n",
" <td>306</td>\n",
" </tr>\n",
" <tr>\n",
" <th>position</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>precision</th>\n",
" <td>0</td>\n",
" <td>4120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>production_unit</th>\n",
" <td>0</td>\n",
" <td>6144</td>\n",
" </tr>\n",
" <tr>\n",
" <th>production_volume</th>\n",
" <td>0</td>\n",
" <td>6014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>province</th>\n",
" <td>2504</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>rec_id</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>status</th>\n",
" <td>2510</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" <tr>\n",
" <th>type \\n permis</th>\n",
" <td>2510</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>year</th>\n",
" <td>0</td>\n",
" <td>6478</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"source rp.org-sources usgs\n",
"carres 2510 0\n",
"cite 0 6478\n",
"commodity 0 6478\n",
"company_name 0 5878\n",
"country 2510 6478\n",
"dmslat 0 5685\n",
"dmslong 0 5686\n",
"expiration 2423 0\n",
"fac_name 0 4854\n",
"fac_type 0 6337\n",
"latitude 0 6478\n",
"localisation 2510 0\n",
"location 0 5478\n",
"longitude 0 6478\n",
"maininvest 0 1551\n",
"mm 0 1190\n",
"notes 0 2239\n",
"octroi 2423 0\n",
"othinvest 0 306\n",
"position 0 6478\n",
"precision 0 4120\n",
"production_unit 0 6144\n",
"production_volume 0 6014\n",
"province 2504 0\n",
"rec_id 0 6478\n",
"status 2510 6478\n",
"type \\n permis 2510 0\n",
"year 0 6478"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_idn = combined_df[combined_df['country'] == 'Congo - Kinshasa']\n",
"fields = combined_df.groupby('source').count().transpose()\n",
"fields"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Series([], Name: source, dtype: int64)"
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"company_names_by_source = df_idn.groupby('company_name')['source'].nunique()\n",
"company_names_by_source.sort(ascending=False)\n",
"company_names_gt1_source = company_names_by_source[company_names_by_source > 1]\n",
"company_names_gt1_source"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"for name, group in df_idn.groupby('company_name')['source']:\n",
" if group.nunique() > 1:\n",
" print(name)\n",
" print(group.value_counts())"
]
},
{
"cell_type": "code",
"execution_count": 121,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"rp.org-sources 0\n",
"usgs 24\n",
"dtype: int64"
]
},
"execution_count": 121,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sources = df_idn.source.unique()\n",
"series = [ pd.Series(df_idn[df_idn['source'] == source].company_name.unique()) for source in sources ]\n",
"df = pd.concat(series, axis=1)\n",
"df.columns = df_idn.source.unique()\n",
"df.count()"
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>rp.org-sources</th>\n",
" <th>usgs</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>NaN</td>\n",
" <td>Interlacs (The Forrest Group)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>NaN</td>\n",
" <td>Cimenterie Nationale SARL</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>NaN</td>\n",
" <td>Cemenkat, (The Forrest Group, and Gecamines)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>NaN</td>\n",
" <td>La Générale des Carrières et des Mines (Gécami...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>NaN</td>\n",
" <td>Lukala Cements Company, (The Forrest Group)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>NaN</td>\n",
" <td>Le Societe pour le Traitement de la Terril de ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>NaN</td>\n",
" <td>Société Minière de Kabolela et de Kipese (SMKK...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>NaN</td>\n",
" <td>Kababankola Mining Company (KMC), Tremalt Ltd....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>NaN</td>\n",
" <td>Société Minière du Congo (Somico SARL), [forme...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>NaN</td>\n",
" <td>Gécamines</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>NaN</td>\n",
" <td>Anvil Mining Congo SARL [Anvil Mining NL (81....</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>NaN</td>\n",
" <td>Compagnie Minera De Sakania SPRL (Comisa), [Fi...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>NaN</td>\n",
" <td>OMGI (55%), EGMF (25%), and Gecamines (25%) jo...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>NaN</td>\n",
" <td>Gécamines, Kinross Gold Corp. and EGMF</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>NaN</td>\n",
" <td>Gécamines and Kumba Resources Ltd. joint venture</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>NaN</td>\n",
" <td>KingamyamboMusonoi Tailings SARL, [Congo Miner...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>NaN</td>\n",
" <td>Tenke Mining Corp.(60%) and Gecamines (40%) jo...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>NaN</td>\n",
" <td>Ruashi Mining [Metorex Ltd.of South Africa, Se...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>NaN</td>\n",
" <td>Société Minière de Bakwanga (MIBA), Government...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>NaN</td>\n",
" <td>Société Aurifère du Kivu et du Maniema S.A.R.L...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>NaN</td>\n",
" <td>Societe de Recherche et d'Exploitation des pet...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>NaN</td>\n",
" <td>Societe Congo-Italienne de Raffinage (SOCIR), ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>NaN</td>\n",
" <td>Zincongo [Adastra Minerals Inc., Zinc Corp. of...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>NaN</td>\n",
" <td>Gecamines</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" rp.org-sources usgs\n",
"0 NaN Interlacs (The Forrest Group)\n",
"1 NaN Cimenterie Nationale SARL\n",
"2 NaN Cemenkat, (The Forrest Group, and Gecamines)\n",
"3 NaN La Générale des Carrières et des Mines (Gécami...\n",
"4 NaN Lukala Cements Company, (The Forrest Group)\n",
"5 NaN Le Societe pour le Traitement de la Terril de ...\n",
"6 NaN Société Minière de Kabolela et de Kipese (SMKK...\n",
"7 NaN Kababankola Mining Company (KMC), Tremalt Ltd....\n",
"8 NaN Société Minière du Congo (Somico SARL), [forme...\n",
"9 NaN Gécamines\n",
"10 NaN Anvil Mining Congo SARL [Anvil Mining NL (81....\n",
"11 NaN Compagnie Minera De Sakania SPRL (Comisa), [Fi...\n",
"12 NaN OMGI (55%), EGMF (25%), and Gecamines (25%) jo...\n",
"13 NaN Gécamines, Kinross Gold Corp. and EGMF\n",
"14 NaN Gécamines and Kumba Resources Ltd. joint venture\n",
"15 NaN KingamyamboMusonoi Tailings SARL, [Congo Miner...\n",
"16 NaN Tenke Mining Corp.(60%) and Gecamines (40%) jo...\n",
"17 NaN Ruashi Mining [Metorex Ltd.of South Africa, Se...\n",
"18 NaN Société Minière de Bakwanga (MIBA), Government...\n",
"19 NaN Société Aurifère du Kivu et du Maniema S.A.R.L...\n",
"20 NaN Societe de Recherche et d'Exploitation des pet...\n",
"21 NaN Societe Congo-Italienne de Raffinage (SOCIR), ...\n",
"22 NaN Zincongo [Adastra Minerals Inc., Zinc Corp. of...\n",
"23 NaN Gecamines"
]
},
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}
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"source": [
"df"
]
}
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