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johntfoster/ibis_example.ipynb

Last active May 6, 2019 20:19
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ibis_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import ibis"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"con = ibis.postgres.connect('premium-west.bazean.com', \n",
" user=os.environ['BAZEAN_POSTGRES_USERNAME'], \n",
" password=os.environ['BAZEAN_POSTGRES_PASSWORD'],\n",
" database='db')"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"p = con.table('production_all', schema='public')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"data = con.execute(p[p.state == 'ND']['date','api','volume_oil_formation_bbls'], limit=None)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>volume_oil_formation_bbls</th>\n",
" </tr>\n",
" <tr>\n",
" <th>api</th>\n",
" <th>date</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>33007000140000</th>\n",
" <th>2010-01-01</th>\n",
" <td>214</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"20\" valign=\"top\">33007000110000</th>\n",
" <th>2010-01-01</th>\n",
" <td>161</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-02-01</th>\n",
" <td>221</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-03-01</th>\n",
" <td>226</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-04-01</th>\n",
" <td>205</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-05-01</th>\n",
" <td>255</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-06-01</th>\n",
" <td>179</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-07-01</th>\n",
" <td>218</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-08-01</th>\n",
" <td>188</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-09-01</th>\n",
" <td>159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-10-01</th>\n",
" <td>142</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-11-01</th>\n",
" <td>143</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-12-01</th>\n",
" <td>159</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-01-01</th>\n",
" <td>145</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-02-01</th>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-03-01</th>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-05-01</th>\n",
" <td>41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-06-01</th>\n",
" <td>247</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-07-01</th>\n",
" <td>257</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-08-01</th>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011-09-01</th>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"9\" valign=\"top\">33007000140000</th>\n",
" <th>2010-02-01</th>\n",
" <td>288</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-03-01</th>\n",
" <td>316</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-04-01</th>\n",
" <td>281</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-05-01</th>\n",
" <td>293</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-06-01</th>\n",
" <td>182</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-07-01</th>\n",
" <td>277</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-08-01</th>\n",
" <td>244</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-09-01</th>\n",
" <td>270</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010-10-01</th>\n",
" <td>242</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"2\" valign=\"top\">33105046950000</th>\n",
" <th>2019-02-01</th>\n",
" <td>12209</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-03-01</th>\n",
" <td>9365</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"7\" valign=\"top\">33105046960000</th>\n",
" <th>2018-09-01</th>\n",
" <td>11122</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-10-01</th>\n",
" <td>14000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-11-01</th>\n",
" <td>15495</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-12-01</th>\n",
" <td>14189</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-01-01</th>\n",
" <td>17189</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-02-01</th>\n",
" <td>10761</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-03-01</th>\n",
" <td>8929</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"7\" valign=\"top\">33105046970000</th>\n",
" <th>2018-09-01</th>\n",
" <td>10324</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-10-01</th>\n",
" <td>14819</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-11-01</th>\n",
" <td>16669</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-12-01</th>\n",
" <td>17243</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-01-01</th>\n",
" <td>14398</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-02-01</th>\n",
" <td>1007</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-03-01</th>\n",
" <td>10835</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"7\" valign=\"top\">33105046980000</th>\n",
" <th>2018-09-01</th>\n",
" <td>11484</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-10-01</th>\n",
" <td>13807</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-11-01</th>\n",
" <td>15280</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-12-01</th>\n",
" <td>17628</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-01-01</th>\n",
" <td>13651</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-02-01</th>\n",
" <td>7418</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-03-01</th>\n",
" <td>5348</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"7\" valign=\"top\">33105047070000</th>\n",
" <th>2018-08-01</th>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-09-01</th>\n",
" <td>754</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-10-01</th>\n",
" <td>23375</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-11-01</th>\n",
" <td>22755</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018-12-01</th>\n",
" <td>31638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-01-01</th>\n",
" <td>27492</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019-02-01</th>\n",
" <td>12792</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1161829 rows × 1 columns</p>\n",
"</div>"
],
"text/plain": [
" volume_oil_formation_bbls\n",
"api date \n",
"33007000140000 2010-01-01 214\n",
"33007000110000 2010-01-01 161\n",
" 2010-02-01 221\n",
" 2010-03-01 226\n",
" 2010-04-01 205\n",
" 2010-05-01 255\n",
" 2010-06-01 179\n",
" 2010-07-01 218\n",
" 2010-08-01 188\n",
" 2010-09-01 159\n",
" 2010-10-01 142\n",
" 2010-11-01 143\n",
" 2010-12-01 159\n",
" 2011-01-01 145\n",
" 2011-02-01 15\n",
" 2011-03-01 2\n",
" 2011-05-01 41\n",
" 2011-06-01 247\n",
" 2011-07-01 257\n",
" 2011-08-01 36\n",
" 2011-09-01 4\n",
"33007000140000 2010-02-01 288\n",
" 2010-03-01 316\n",
" 2010-04-01 281\n",
" 2010-05-01 293\n",
" 2010-06-01 182\n",
" 2010-07-01 277\n",
" 2010-08-01 244\n",
" 2010-09-01 270\n",
" 2010-10-01 242\n",
"... ...\n",
"33105046950000 2019-02-01 12209\n",
" 2019-03-01 9365\n",
"33105046960000 2018-09-01 11122\n",
" 2018-10-01 14000\n",
" 2018-11-01 15495\n",
" 2018-12-01 14189\n",
" 2019-01-01 17189\n",
" 2019-02-01 10761\n",
" 2019-03-01 8929\n",
"33105046970000 2018-09-01 10324\n",
" 2018-10-01 14819\n",
" 2018-11-01 16669\n",
" 2018-12-01 17243\n",
" 2019-01-01 14398\n",
" 2019-02-01 1007\n",
" 2019-03-01 10835\n",
"33105046980000 2018-09-01 11484\n",
" 2018-10-01 13807\n",
" 2018-11-01 15280\n",
" 2018-12-01 17628\n",
" 2019-01-01 13651\n",
" 2019-02-01 7418\n",
" 2019-03-01 5348\n",
"33105047070000 2018-08-01 0\n",
" 2018-09-01 754\n",
" 2018-10-01 23375\n",
" 2018-11-01 22755\n",
" 2018-12-01 31638\n",
" 2019-01-01 27492\n",
" 2019-02-01 12792\n",
"\n",
"[1161829 rows x 1 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.set_index(['api','date'])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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