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ZeccaLehn/gistExplore.ipynb

Last active January 11, 2023 14:32
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Blog: Level-Up using Gists with Python
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gistExplore.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Username:zeccalehn\n",
"Password (blank for public only):\n"
]
},
{
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" <td>2018-12-06T03:52:03Z</td>\n",
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" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
" <td>2018-07-05T02:11:59Z</td>\n",
" <td>Multiple ETF/ETN Tickers and Stats in Python</td>\n",
" <td>{'etfStats.ipynb': {'filename': 'etfStats.ipyn...</td>\n",
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" <td>2018-07-05T02:11:59Z</td>\n",
" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
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" <th>2</th>\n",
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" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" <td>2018-05-14T00:28:52Z</td>\n",
" <td>Download multiple stocks with Python Pandas</td>\n",
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" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" <td>https://gist.github.com/9d4946bf1fe07c27c3ad10...</td>\n",
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" <td>2018-12-06T02:45:51Z</td>\n",
" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
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" <td>0</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" <td>2018-03-22T03:01:47Z</td>\n",
" <td>Automatic GPUs: A reproducible R / Python appr...</td>\n",
" <td>{'RandPythonCondaGPU.txt': {'filename': 'RandP...</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" <td>https://gist.github.com/3e4ebfbd3c42edc6264b09...</td>\n",
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" <td>2018-03-22T03:01:47Z</td>\n",
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" <td>https://api.github.com/gists/de42e70660e54f346...</td>\n",
" <td>2018-03-16T17:19:14Z</td>\n",
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" <td>1</td>\n",
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" <td>https://api.github.com/gists/c49ccc07af115e3de...</td>\n",
" <td>2017-12-30T22:06:55Z</td>\n",
" <td>Py: Adjust Splits and Dividends from Real Pric...</td>\n",
" <td>{'pythonActualPrice.ipynb': {'filename': 'pyth...</td>\n",
" <td>https://api.github.com/gists/c49ccc07af115e3de...</td>\n",
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" <td>0</td>\n",
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" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" <td>2017-11-16T23:21:49Z</td>\n",
" <td>Download all files within directory tree in Py...</td>\n",
" <td>{'downloadTree.md': {'filename': 'downloadTree...</td>\n",
" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" <td>https://gist.github.com/61b73077d780a56d40cdda...</td>\n",
" <td>https://gist.github.com/61b73077d780a56d40cdda...</td>\n",
" <td>https://gist.github.com/61b73077d780a56d40cdda...</td>\n",
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" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-11-17T02:16:45Z</td>\n",
" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" <td>None</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/d497fb3b2f8718699...</td>\n",
" <td>https://api.github.com/gists/d497fb3b2f8718699...</td>\n",
" <td>2017-10-19T08:26:27Z</td>\n",
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" <td>{'binomialCoins': {'filename': 'binomialCoins'...</td>\n",
" <td>https://api.github.com/gists/d497fb3b2f8718699...</td>\n",
" <td>https://gist.github.com/d497fb3b2f8718699079cb...</td>\n",
" <td>https://gist.github.com/d497fb3b2f8718699079cb...</td>\n",
" <td>https://gist.github.com/d497fb3b2f8718699079cb...</td>\n",
" <td>d497fb3b2f8718699079cb9288f0d29f</td>\n",
" <td>MDQ6R2lzdGQ0OTdmYjNiMmY4NzE4Njk5MDc5Y2I5Mjg4Zj...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-10-19T08:26:27Z</td>\n",
" <td>https://api.github.com/gists/d497fb3b2f8718699...</td>\n",
" <td>None</td>\n",
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" <th>8</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/0cd711b7c513de9a8...</td>\n",
" <td>https://api.github.com/gists/0cd711b7c513de9a8...</td>\n",
" <td>2017-10-12T09:27:47Z</td>\n",
" <td>Constrained Optimization in R</td>\n",
" <td>{'constrainedR.md': {'filename': 'constrainedR...</td>\n",
" <td>https://api.github.com/gists/0cd711b7c513de9a8...</td>\n",
" <td>https://gist.github.com/0cd711b7c513de9a8695c2...</td>\n",
" <td>https://gist.github.com/0cd711b7c513de9a8695c2...</td>\n",
" <td>https://gist.github.com/0cd711b7c513de9a8695c2...</td>\n",
" <td>0cd711b7c513de9a8695c2f8679943d9</td>\n",
" <td>MDQ6R2lzdDBjZDcxMWI3YzUxM2RlOWE4Njk1YzJmODY3OT...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-10-12T09:28:13Z</td>\n",
" <td>https://api.github.com/gists/0cd711b7c513de9a8...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>0</td>\n",
" <td>https://api.github.com/gists/c93150bbcae7cae45...</td>\n",
" <td>https://api.github.com/gists/c93150bbcae7cae45...</td>\n",
" <td>2017-10-11T04:55:47Z</td>\n",
" <td>Install and Load Multiple Packages R</td>\n",
" <td>{'installR': {'filename': 'installR', 'type': ...</td>\n",
" <td>https://api.github.com/gists/c93150bbcae7cae45...</td>\n",
" <td>https://gist.github.com/c93150bbcae7cae459fa69...</td>\n",
" <td>https://gist.github.com/c93150bbcae7cae459fa69...</td>\n",
" <td>https://gist.github.com/c93150bbcae7cae459fa69...</td>\n",
" <td>c93150bbcae7cae459fa69e8dfd07a12</td>\n",
" <td>MDQ6R2lzdGM5MzE1MGJiY2FlN2NhZTQ1OWZhNjllOGRmZD...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-10-11T04:55:47Z</td>\n",
" <td>https://api.github.com/gists/c93150bbcae7cae45...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/849ae412247606079...</td>\n",
" <td>https://api.github.com/gists/849ae412247606079...</td>\n",
" <td>2017-10-01T21:19:04Z</td>\n",
" <td>Binomial Probabilities in R using Manipulate P...</td>\n",
" <td>{'dynamicProbability.md': {'filename': 'dynami...</td>\n",
" <td>https://api.github.com/gists/849ae412247606079...</td>\n",
" <td>https://gist.github.com/849ae412247606079169af...</td>\n",
" <td>https://gist.github.com/849ae412247606079169af...</td>\n",
" <td>https://gist.github.com/849ae412247606079169af...</td>\n",
" <td>849ae412247606079169af28b7f003b2</td>\n",
" <td>MDQ6R2lzdDg0OWFlNDEyMjQ3NjA2MDc5MTY5YWYyOGI3Zj...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-10-01T21:19:26Z</td>\n",
" <td>https://api.github.com/gists/849ae412247606079...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/e54a33bb3233f9e35...</td>\n",
" <td>https://api.github.com/gists/e54a33bb3233f9e35...</td>\n",
" <td>2017-10-01T04:41:54Z</td>\n",
" <td>Monte Hall Simulation -- Goat or Ferrari?</td>\n",
" <td>{'monteHall.md': {'filename': 'monteHall.md', ...</td>\n",
" <td>https://api.github.com/gists/e54a33bb3233f9e35...</td>\n",
" <td>https://gist.github.com/e54a33bb3233f9e35164db...</td>\n",
" <td>https://gist.github.com/e54a33bb3233f9e35164db...</td>\n",
" <td>https://gist.github.com/e54a33bb3233f9e35164db...</td>\n",
" <td>e54a33bb3233f9e35164dbbd4287245e</td>\n",
" <td>MDQ6R2lzdGU1NGEzM2JiMzIzM2Y5ZTM1MTY0ZGJiZDQyOD...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-10-01T04:48:28Z</td>\n",
" <td>https://api.github.com/gists/e54a33bb3233f9e35...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/06d85adb49d3dbae2...</td>\n",
" <td>https://api.github.com/gists/06d85adb49d3dbae2...</td>\n",
" <td>2017-09-29T17:56:07Z</td>\n",
" <td>Function Returning List of Multiple Objects in R</td>\n",
" <td>{'returnList.md': {'filename': 'returnList.md'...</td>\n",
" <td>https://api.github.com/gists/06d85adb49d3dbae2...</td>\n",
" <td>https://gist.github.com/06d85adb49d3dbae2a4571...</td>\n",
" <td>https://gist.github.com/06d85adb49d3dbae2a4571...</td>\n",
" <td>https://gist.github.com/06d85adb49d3dbae2a4571...</td>\n",
" <td>06d85adb49d3dbae2a457141ce691b5b</td>\n",
" <td>MDQ6R2lzdDA2ZDg1YWRiNDlkM2RiYWUyYTQ1NzE0MWNlNj...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-09-29T17:57:16Z</td>\n",
" <td>https://api.github.com/gists/06d85adb49d3dbae2...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" <td>2017-09-25T23:21:41Z</td>\n",
" <td>Python Download CSV from Gist (MTCARS DataSet)</td>\n",
" <td>{'readCsvPython.md': {'filename': 'readCsvPyth...</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" <td>https://gist.github.com/4e06d2575eb9589dbe8c36...</td>\n",
" <td>https://gist.github.com/4e06d2575eb9589dbe8c36...</td>\n",
" <td>https://gist.github.com/4e06d2575eb9589dbe8c36...</td>\n",
" <td>4e06d2575eb9589dbe8c365d61cb056c</td>\n",
" <td>MDQ6R2lzdDRlMDZkMjU3NWViOTU4OWRiZThjMzY1ZDYxY2...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-09-25T23:38:19Z</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/3da83ca94309e88ec...</td>\n",
" <td>https://api.github.com/gists/3da83ca94309e88ec...</td>\n",
" <td>2017-09-21T22:16:04Z</td>\n",
" <td>Census &amp; Money 2017 Top 100 Places (Fips/Zips/...</td>\n",
" <td>{'Final_Money_100.csv': {'filename': 'Final_Mo...</td>\n",
" <td>https://api.github.com/gists/3da83ca94309e88ec...</td>\n",
" <td>https://gist.github.com/3da83ca94309e88ec0babe...</td>\n",
" <td>https://gist.github.com/3da83ca94309e88ec0babe...</td>\n",
" <td>https://gist.github.com/3da83ca94309e88ec0babe...</td>\n",
" <td>3da83ca94309e88ec0babe7707fc3e04</td>\n",
" <td>MDQ6R2lzdDNkYTgzY2E5NDMwOWU4OGVjMGJhYmU3NzA3Zm...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-09-25T23:19:22Z</td>\n",
" <td>https://api.github.com/gists/3da83ca94309e88ec...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/e950eab0c07a2891e...</td>\n",
" <td>https://api.github.com/gists/e950eab0c07a2891e...</td>\n",
" <td>2017-06-19T22:14:57Z</td>\n",
" <td>Aggregate versus merge MTCARS with R data.table</td>\n",
" <td>{'aggregateVersusMerge.R': {'filename': 'aggre...</td>\n",
" <td>https://api.github.com/gists/e950eab0c07a2891e...</td>\n",
" <td>https://gist.github.com/e950eab0c07a2891e912f9...</td>\n",
" <td>https://gist.github.com/e950eab0c07a2891e912f9...</td>\n",
" <td>https://gist.github.com/e950eab0c07a2891e912f9...</td>\n",
" <td>e950eab0c07a2891e912f9a50d01f055</td>\n",
" <td>MDQ6R2lzdGU5NTBlYWIwYzA3YTI4OTFlOTEyZjlhNTBkMD...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-06-19T22:18:37Z</td>\n",
" <td>https://api.github.com/gists/e950eab0c07a2891e...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/b6b543d5564b747a3...</td>\n",
" <td>https://api.github.com/gists/b6b543d5564b747a3...</td>\n",
" <td>2017-05-03T01:32:18Z</td>\n",
" <td>Setting Variables in an R Anonymous Function</td>\n",
" <td>{'anonymousR': {'filename': 'anonymousR', 'typ...</td>\n",
" <td>https://api.github.com/gists/b6b543d5564b747a3...</td>\n",
" <td>https://gist.github.com/b6b543d5564b747a3d5846...</td>\n",
" <td>https://gist.github.com/b6b543d5564b747a3d5846...</td>\n",
" <td>https://gist.github.com/b6b543d5564b747a3d5846...</td>\n",
" <td>b6b543d5564b747a3d5846a93d1f6433</td>\n",
" <td>MDQ6R2lzdGI2YjU0M2Q1NTY0Yjc0N2EzZDU4NDZhOTNkMW...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-05-03T01:32:50Z</td>\n",
" <td>https://api.github.com/gists/b6b543d5564b747a3...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/5e64403ed44e79ad2...</td>\n",
" <td>https://api.github.com/gists/5e64403ed44e79ad2...</td>\n",
" <td>2017-05-02T02:01:07Z</td>\n",
" <td>Exponential Regression Test in R</td>\n",
" <td>{'exponentialRegression.r': {'filename': 'expo...</td>\n",
" <td>https://api.github.com/gists/5e64403ed44e79ad2...</td>\n",
" <td>https://gist.github.com/5e64403ed44e79ad27b5a1...</td>\n",
" <td>https://gist.github.com/5e64403ed44e79ad27b5a1...</td>\n",
" <td>https://gist.github.com/5e64403ed44e79ad27b5a1...</td>\n",
" <td>5e64403ed44e79ad27b5a144cfa7ba78</td>\n",
" <td>MDQ6R2lzdDVlNjQ0MDNlZDQ0ZTc5YWQyN2I1YTE0NGNmYT...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-05-02T02:02:12Z</td>\n",
" <td>https://api.github.com/gists/5e64403ed44e79ad2...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>1</td>\n",
" <td>https://api.github.com/gists/81e32b3d0c5a71f87...</td>\n",
" <td>https://api.github.com/gists/81e32b3d0c5a71f87...</td>\n",
" <td>2017-05-01T19:04:23Z</td>\n",
" <td>Set logic in R</td>\n",
" <td>{'setExamples.r': {'filename': 'setExamples.r'...</td>\n",
" <td>https://api.github.com/gists/81e32b3d0c5a71f87...</td>\n",
" <td>https://gist.github.com/81e32b3d0c5a71f87ef76b...</td>\n",
" <td>https://gist.github.com/81e32b3d0c5a71f87ef76b...</td>\n",
" <td>https://gist.github.com/81e32b3d0c5a71f87ef76b...</td>\n",
" <td>81e32b3d0c5a71f87ef76b0c97d99acb</td>\n",
" <td>MDQ6R2lzdDgxZTMyYjNkMGM1YTcxZjg3ZWY3NmIwYzk3ZD...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-05-03T00:36:00Z</td>\n",
" <td>https://api.github.com/gists/81e32b3d0c5a71f87...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/d7f3330b1a2088f17...</td>\n",
" <td>https://api.github.com/gists/d7f3330b1a2088f17...</td>\n",
" <td>2017-01-11T16:17:38Z</td>\n",
" <td>Return Multiple Objects with Apply Function in...</td>\n",
" <td>{'ApplyMultiple.r': {'filename': 'ApplyMultipl...</td>\n",
" <td>https://api.github.com/gists/d7f3330b1a2088f17...</td>\n",
" <td>https://gist.github.com/d7f3330b1a2088f1729dcf...</td>\n",
" <td>https://gist.github.com/d7f3330b1a2088f1729dcf...</td>\n",
" <td>https://gist.github.com/d7f3330b1a2088f1729dcf...</td>\n",
" <td>d7f3330b1a2088f1729dcf6dea1fd875</td>\n",
" <td>MDQ6R2lzdGQ3ZjMzMzBiMWEyMDg4ZjE3MjlkY2Y2ZGVhMW...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-01-11T19:32:14Z</td>\n",
" <td>https://api.github.com/gists/d7f3330b1a2088f17...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/59b50caa72d79fc1e...</td>\n",
" <td>https://api.github.com/gists/59b50caa72d79fc1e...</td>\n",
" <td>2017-01-01T04:10:17Z</td>\n",
" <td>Multiple Security Downloader with D3.js Plot</td>\n",
" <td>{'MultipleSecurityD3.r': {'filename': 'Multipl...</td>\n",
" <td>https://api.github.com/gists/59b50caa72d79fc1e...</td>\n",
" <td>https://gist.github.com/59b50caa72d79fc1e8b622...</td>\n",
" <td>https://gist.github.com/59b50caa72d79fc1e8b622...</td>\n",
" <td>https://gist.github.com/59b50caa72d79fc1e8b622...</td>\n",
" <td>59b50caa72d79fc1e8b622b1ed2ee69c</td>\n",
" <td>MDQ6R2lzdDU5YjUwY2FhNzJkNzlmYzFlOGI2MjJiMWVkMm...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-02-18T16:50:51Z</td>\n",
" <td>https://api.github.com/gists/59b50caa72d79fc1e...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/61735aec7c2f69d6d...</td>\n",
" <td>https://api.github.com/gists/61735aec7c2f69d6d...</td>\n",
" <td>2016-12-19T01:33:12Z</td>\n",
" <td>[R] Setting variables dynamically via strings ...</td>\n",
" <td>{'dynamicStringSetting.R': {'filename': 'dynam...</td>\n",
" <td>https://api.github.com/gists/61735aec7c2f69d6d...</td>\n",
" <td>https://gist.github.com/61735aec7c2f69d6d0cde2...</td>\n",
" <td>https://gist.github.com/61735aec7c2f69d6d0cde2...</td>\n",
" <td>https://gist.github.com/61735aec7c2f69d6d0cde2...</td>\n",
" <td>61735aec7c2f69d6d0cde2d83afa4372</td>\n",
" <td>MDQ6R2lzdDYxNzM1YWVjN2MyZjY5ZDZkMGNkZTJkODNhZm...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-12-19T01:33:12Z</td>\n",
" <td>https://api.github.com/gists/61735aec7c2f69d6d...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/a86f4e7e88535615c...</td>\n",
" <td>https://api.github.com/gists/a86f4e7e88535615c...</td>\n",
" <td>2016-11-23T21:25:00Z</td>\n",
" <td>POSIXct Roundtrip (Date Conversions)</td>\n",
" <td>{'posixRoundTrip.r': {'filename': 'posixRoundT...</td>\n",
" <td>https://api.github.com/gists/a86f4e7e88535615c...</td>\n",
" <td>https://gist.github.com/a86f4e7e88535615c3755b...</td>\n",
" <td>https://gist.github.com/a86f4e7e88535615c3755b...</td>\n",
" <td>https://gist.github.com/a86f4e7e88535615c3755b...</td>\n",
" <td>a86f4e7e88535615c3755b3198e5aa59</td>\n",
" <td>MDQ6R2lzdGE4NmY0ZTdlODg1MzU2MTVjMzc1NWIzMTk4ZT...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-11-23T21:25:00Z</td>\n",
" <td>https://api.github.com/gists/a86f4e7e88535615c...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/769e2cbe055b5f87e...</td>\n",
" <td>https://api.github.com/gists/769e2cbe055b5f87e...</td>\n",
" <td>2016-09-09T18:13:01Z</td>\n",
" <td>[R] Adjusted Returns with Checked Lag: Yahoo F...</td>\n",
" <td>{'laggedTicker.ipynb': {'filename': 'laggedTic...</td>\n",
" <td>https://api.github.com/gists/769e2cbe055b5f87e...</td>\n",
" <td>https://gist.github.com/769e2cbe055b5f87ea7adb...</td>\n",
" <td>https://gist.github.com/769e2cbe055b5f87ea7adb...</td>\n",
" <td>https://gist.github.com/769e2cbe055b5f87ea7adb...</td>\n",
" <td>769e2cbe055b5f87ea7adb4763894beb</td>\n",
" <td>MDQ6R2lzdDc2OWUyY2JlMDU1YjVmODdlYTdhZGI0NzYzOD...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-09-09T18:13:02Z</td>\n",
" <td>https://api.github.com/gists/769e2cbe055b5f87e...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/a805be84fea59cc2a...</td>\n",
" <td>https://api.github.com/gists/a805be84fea59cc2a...</td>\n",
" <td>2016-09-09T03:42:46Z</td>\n",
" <td>[R] Baltic Dry Index (BDI) versus SP500 Lagged...</td>\n",
" <td>{'balticDry_SP500.ipynb': {'filename': 'baltic...</td>\n",
" <td>https://api.github.com/gists/a805be84fea59cc2a...</td>\n",
" <td>https://gist.github.com/a805be84fea59cc2a7e4ef...</td>\n",
" <td>https://gist.github.com/a805be84fea59cc2a7e4ef...</td>\n",
" <td>https://gist.github.com/a805be84fea59cc2a7e4ef...</td>\n",
" <td>a805be84fea59cc2a7e4ef93f47e70d1</td>\n",
" <td>MDQ6R2lzdGE4MDViZTg0ZmVhNTljYzJhN2U0ZWY5M2Y0N2...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-09-09T03:42:46Z</td>\n",
" <td>https://api.github.com/gists/a805be84fea59cc2a...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/f1a5aac1f45cce380...</td>\n",
" <td>https://api.github.com/gists/f1a5aac1f45cce380...</td>\n",
" <td>2016-08-15T20:02:04Z</td>\n",
" <td>[R] Download All Tickers from both Google and ...</td>\n",
" <td>{'tickerDownloads.ipynb': {'filename': 'ticker...</td>\n",
" <td>https://api.github.com/gists/f1a5aac1f45cce380...</td>\n",
" <td>https://gist.github.com/f1a5aac1f45cce380ea22c...</td>\n",
" <td>https://gist.github.com/f1a5aac1f45cce380ea22c...</td>\n",
" <td>https://gist.github.com/f1a5aac1f45cce380ea22c...</td>\n",
" <td>f1a5aac1f45cce380ea22cf3e0fc27a2</td>\n",
" <td>MDQ6R2lzdGYxYTVhYWMxZjQ1Y2NlMzgwZWEyMmNmM2UwZm...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-08-17T01:03:28Z</td>\n",
" <td>https://api.github.com/gists/f1a5aac1f45cce380...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" <td>2016-08-02T19:07:49Z</td>\n",
" <td>Python working directory management</td>\n",
" <td>{'workingDirPython.md': {'filename': 'workingD...</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" <td>https://gist.github.com/fb76acb246c2507c207b3a...</td>\n",
" <td>https://gist.github.com/fb76acb246c2507c207b3a...</td>\n",
" <td>https://gist.github.com/fb76acb246c2507c207b3a...</td>\n",
" <td>fb76acb246c2507c207b3a4e5352a2f9</td>\n",
" <td>MDQ6R2lzdGZiNzZhY2IyNDZjMjUwN2MyMDdiM2E0ZTUzNT...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2017-09-25T23:58:13Z</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/3470c509ffa430c95...</td>\n",
" <td>https://api.github.com/gists/3470c509ffa430c95...</td>\n",
" <td>2016-07-08T20:06:11Z</td>\n",
" <td>Seasonally Adjusted Forecasting in R and Anoma...</td>\n",
" <td>{'seasonalForecasting.ipynb': {'filename': 'se...</td>\n",
" <td>https://api.github.com/gists/3470c509ffa430c95...</td>\n",
" <td>https://gist.github.com/3470c509ffa430c955b352...</td>\n",
" <td>https://gist.github.com/3470c509ffa430c955b352...</td>\n",
" <td>https://gist.github.com/3470c509ffa430c955b352...</td>\n",
" <td>3470c509ffa430c955b35202a8a2aef6</td>\n",
" <td>MDQ6R2lzdDM0NzBjNTA5ZmZhNDMwYzk1NWIzNTIwMmE4YT...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-09-03T16:31:02Z</td>\n",
" <td>https://api.github.com/gists/3470c509ffa430c95...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" <td>2016-06-28T22:12:43Z</td>\n",
" <td>[Python 3] In-Memory XLS Yahoo Finance Stock D...</td>\n",
" <td>{'XLSDownloader.ipynb': {'filename': 'XLSDownl...</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" <td>https://gist.github.com/dc5b4b48af6c44f596e888...</td>\n",
" <td>https://gist.github.com/dc5b4b48af6c44f596e888...</td>\n",
" <td>https://gist.github.com/dc5b4b48af6c44f596e888...</td>\n",
" <td>dc5b4b48af6c44f596e888901577e8a8</td>\n",
" <td>MDQ6R2lzdGRjNWI0YjQ4YWY2YzQ0ZjU5NmU4ODg5MDE1Nz...</td>\n",
" <td>{'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'...</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>2016-06-29T20:18:11Z</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" <td>None</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>0</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" <td>2016-06-28T20:12:54Z</td>\n",
" <td>Python XLS In-Memory Downloader</td>\n",
" <td>{'XLSinMemory.py': {'filename': 'XLSinMemory.p...</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" <td>https://gist.github.com/8acf4342c89359b31f822a...</td>\n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
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"\n",
" description \\\n",
"0 Test Dual Gist \n",
"1 Multiple ETF/ETN Tickers and Stats in Python \n",
"2 Download multiple stocks with Python Pandas \n",
"3 Automatic GPUs: A reproducible R / Python appr... \n",
"4 GCP/GCloud VM setup running R/Python using Ana... \n",
"5 Py: Adjust Splits and Dividends from Real Pric... \n",
"6 Download all files within directory tree in Py... \n",
"7 Likelihood and coin-flips (Combinatorics and L... \n",
"8 Constrained Optimization in R \n",
"9 Install and Load Multiple Packages R \n",
"10 Binomial Probabilities in R using Manipulate P... \n",
"11 Monte Hall Simulation -- Goat or Ferrari? \n",
"12 Function Returning List of Multiple Objects in R \n",
"13 Python Download CSV from Gist (MTCARS DataSet) \n",
"14 Census & Money 2017 Top 100 Places (Fips/Zips/... \n",
"15 Aggregate versus merge MTCARS with R data.table \n",
"16 Setting Variables in an R Anonymous Function \n",
"17 Exponential Regression Test in R \n",
"18 Set logic in R \n",
"19 Return Multiple Objects with Apply Function in... \n",
"20 Multiple Security Downloader with D3.js Plot \n",
"21 [R] Setting variables dynamically via strings ... \n",
"22 POSIXct Roundtrip (Date Conversions) \n",
"23 [R] Adjusted Returns with Checked Lag: Yahoo F... \n",
"24 [R] Baltic Dry Index (BDI) versus SP500 Lagged... \n",
"25 [R] Download All Tickers from both Google and ... \n",
"26 Python working directory management \n",
"27 Seasonally Adjusted Forecasting in R and Anoma... \n",
"28 [Python 3] In-Memory XLS Yahoo Finance Stock D... \n",
"29 Python XLS In-Memory Downloader \n",
"\n",
" files \\\n",
"0 {'helloTest.py': {'filename': 'helloTest.py', ... \n",
"1 {'etfStats.ipynb': {'filename': 'etfStats.ipyn... \n",
"2 {'multipleStocks.py': {'filename': 'multipleSt... \n",
"3 {'RandPythonCondaGPU.txt': {'filename': 'RandP... \n",
"4 {'condaRandPython.txt': {'filename': 'condaRan... \n",
"5 {'pythonActualPrice.ipynb': {'filename': 'pyth... \n",
"6 {'downloadTree.md': {'filename': 'downloadTree... \n",
"7 {'binomialCoins': {'filename': 'binomialCoins'... \n",
"8 {'constrainedR.md': {'filename': 'constrainedR... \n",
"9 {'installR': {'filename': 'installR', 'type': ... \n",
"10 {'dynamicProbability.md': {'filename': 'dynami... \n",
"11 {'monteHall.md': {'filename': 'monteHall.md', ... \n",
"12 {'returnList.md': {'filename': 'returnList.md'... \n",
"13 {'readCsvPython.md': {'filename': 'readCsvPyth... \n",
"14 {'Final_Money_100.csv': {'filename': 'Final_Mo... \n",
"15 {'aggregateVersusMerge.R': {'filename': 'aggre... \n",
"16 {'anonymousR': {'filename': 'anonymousR', 'typ... \n",
"17 {'exponentialRegression.r': {'filename': 'expo... \n",
"18 {'setExamples.r': {'filename': 'setExamples.r'... \n",
"19 {'ApplyMultiple.r': {'filename': 'ApplyMultipl... \n",
"20 {'MultipleSecurityD3.r': {'filename': 'Multipl... \n",
"21 {'dynamicStringSetting.R': {'filename': 'dynam... \n",
"22 {'posixRoundTrip.r': {'filename': 'posixRoundT... \n",
"23 {'laggedTicker.ipynb': {'filename': 'laggedTic... \n",
"24 {'balticDry_SP500.ipynb': {'filename': 'baltic... \n",
"25 {'tickerDownloads.ipynb': {'filename': 'ticker... \n",
"26 {'workingDirPython.md': {'filename': 'workingD... \n",
"27 {'seasonalForecasting.ipynb': {'filename': 'se... \n",
"28 {'XLSDownloader.ipynb': {'filename': 'XLSDownl... \n",
"29 {'XLSinMemory.py': {'filename': 'XLSinMemory.p... \n",
"\n",
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"24 a805be84fea59cc2a7e4ef93f47e70d1 \n",
"25 f1a5aac1f45cce380ea22cf3e0fc27a2 \n",
"26 fb76acb246c2507c207b3a4e5352a2f9 \n",
"27 3470c509ffa430c955b35202a8a2aef6 \n",
"28 dc5b4b48af6c44f596e888901577e8a8 \n",
"29 8acf4342c89359b31f822a0d9fc068d3 \n",
"\n",
" node_id \\\n",
"0 MDQ6R2lzdDdmMWExMGYxMjk4OTIyNWUwZWE5NTc1NzkzOT... \n",
"1 MDQ6R2lzdDYxYWQ0YWFlNTMyNGU0NWM2M2RjZWE2N2MwMD... \n",
"2 MDQ6R2lzdDlkNDk0NmJmMWZlMDdjMjdjM2FkMTBlZjgzMD... \n",
"3 MDQ6R2lzdDNlNGViZmJkM2M0MmVkYzYyNjRiMDlmZjMwYT... \n",
"4 MDQ6R2lzdGRlNDJlNzA2NjBlNTRmMzQ2MjgyNDlmYWU3ZD... \n",
"5 MDQ6R2lzdGM0OWNjYzA3YWYxMTVlM2RlYzg3OGVkOGE2OG... \n",
"6 MDQ6R2lzdDYxYjczMDc3ZDc4MGE1NmQ0MGNkZGE2ZGZlMz... \n",
"7 MDQ6R2lzdGQ0OTdmYjNiMmY4NzE4Njk5MDc5Y2I5Mjg4Zj... \n",
"8 MDQ6R2lzdDBjZDcxMWI3YzUxM2RlOWE4Njk1YzJmODY3OT... \n",
"9 MDQ6R2lzdGM5MzE1MGJiY2FlN2NhZTQ1OWZhNjllOGRmZD... \n",
"10 MDQ6R2lzdDg0OWFlNDEyMjQ3NjA2MDc5MTY5YWYyOGI3Zj... \n",
"11 MDQ6R2lzdGU1NGEzM2JiMzIzM2Y5ZTM1MTY0ZGJiZDQyOD... \n",
"12 MDQ6R2lzdDA2ZDg1YWRiNDlkM2RiYWUyYTQ1NzE0MWNlNj... \n",
"13 MDQ6R2lzdDRlMDZkMjU3NWViOTU4OWRiZThjMzY1ZDYxY2... \n",
"14 MDQ6R2lzdDNkYTgzY2E5NDMwOWU4OGVjMGJhYmU3NzA3Zm... \n",
"15 MDQ6R2lzdGU5NTBlYWIwYzA3YTI4OTFlOTEyZjlhNTBkMD... \n",
"16 MDQ6R2lzdGI2YjU0M2Q1NTY0Yjc0N2EzZDU4NDZhOTNkMW... \n",
"17 MDQ6R2lzdDVlNjQ0MDNlZDQ0ZTc5YWQyN2I1YTE0NGNmYT... \n",
"18 MDQ6R2lzdDgxZTMyYjNkMGM1YTcxZjg3ZWY3NmIwYzk3ZD... \n",
"19 MDQ6R2lzdGQ3ZjMzMzBiMWEyMDg4ZjE3MjlkY2Y2ZGVhMW... \n",
"20 MDQ6R2lzdDU5YjUwY2FhNzJkNzlmYzFlOGI2MjJiMWVkMm... \n",
"21 MDQ6R2lzdDYxNzM1YWVjN2MyZjY5ZDZkMGNkZTJkODNhZm... \n",
"22 MDQ6R2lzdGE4NmY0ZTdlODg1MzU2MTVjMzc1NWIzMTk4ZT... \n",
"23 MDQ6R2lzdDc2OWUyY2JlMDU1YjVmODdlYTdhZGI0NzYzOD... \n",
"24 MDQ6R2lzdGE4MDViZTg0ZmVhNTljYzJhN2U0ZWY5M2Y0N2... \n",
"25 MDQ6R2lzdGYxYTVhYWMxZjQ1Y2NlMzgwZWEyMmNmM2UwZm... \n",
"26 MDQ6R2lzdGZiNzZhY2IyNDZjMjUwN2MyMDdiM2E0ZTUzNT... \n",
"27 MDQ6R2lzdDM0NzBjNTA5ZmZhNDMwYzk1NWIzNTIwMmE4YT... \n",
"28 MDQ6R2lzdGRjNWI0YjQ4YWY2YzQ0ZjU5NmU4ODg5MDE1Nz... \n",
"29 MDQ6R2lzdDhhY2Y0MzQyYzg5MzU5YjMxZjgyMmEwZDlmYz... \n",
"\n",
" owner public truncated \\\n",
"0 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"1 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"2 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"3 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"4 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"5 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"6 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"7 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"8 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"9 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"10 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"11 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"12 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"13 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"14 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"15 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"16 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"17 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"18 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"19 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"20 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"21 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"22 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"23 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"24 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"25 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"26 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"27 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"28 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"29 {'node_id': 'MDQ6VXNlcjc1NzExODQ=', 'html_url'... True False \n",
"\n",
" updated_at url \\\n",
"0 2018-12-06T03:52:03Z https://api.github.com/gists/7f1a10f12989225e0... \n",
"1 2018-07-05T02:11:59Z https://api.github.com/gists/61ad4aae5324e45c6... \n",
"2 2018-12-06T02:45:51Z https://api.github.com/gists/9d4946bf1fe07c27c... \n",
"3 2018-03-22T03:01:47Z https://api.github.com/gists/3e4ebfbd3c42edc62... \n",
"4 2018-03-16T17:19:44Z https://api.github.com/gists/de42e70660e54f346... \n",
"5 2017-12-30T22:11:27Z https://api.github.com/gists/c49ccc07af115e3de... \n",
"6 2017-11-17T02:16:45Z https://api.github.com/gists/61b73077d780a56d4... \n",
"7 2017-10-19T08:26:27Z https://api.github.com/gists/d497fb3b2f8718699... \n",
"8 2017-10-12T09:28:13Z https://api.github.com/gists/0cd711b7c513de9a8... \n",
"9 2017-10-11T04:55:47Z https://api.github.com/gists/c93150bbcae7cae45... \n",
"10 2017-10-01T21:19:26Z https://api.github.com/gists/849ae412247606079... \n",
"11 2017-10-01T04:48:28Z https://api.github.com/gists/e54a33bb3233f9e35... \n",
"12 2017-09-29T17:57:16Z https://api.github.com/gists/06d85adb49d3dbae2... \n",
"13 2017-09-25T23:38:19Z https://api.github.com/gists/4e06d2575eb9589db... \n",
"14 2017-09-25T23:19:22Z https://api.github.com/gists/3da83ca94309e88ec... \n",
"15 2017-06-19T22:18:37Z https://api.github.com/gists/e950eab0c07a2891e... \n",
"16 2017-05-03T01:32:50Z https://api.github.com/gists/b6b543d5564b747a3... \n",
"17 2017-05-02T02:02:12Z https://api.github.com/gists/5e64403ed44e79ad2... \n",
"18 2017-05-03T00:36:00Z https://api.github.com/gists/81e32b3d0c5a71f87... \n",
"19 2017-01-11T19:32:14Z https://api.github.com/gists/d7f3330b1a2088f17... \n",
"20 2017-02-18T16:50:51Z https://api.github.com/gists/59b50caa72d79fc1e... \n",
"21 2016-12-19T01:33:12Z https://api.github.com/gists/61735aec7c2f69d6d... \n",
"22 2016-11-23T21:25:00Z https://api.github.com/gists/a86f4e7e88535615c... \n",
"23 2016-09-09T18:13:02Z https://api.github.com/gists/769e2cbe055b5f87e... \n",
"24 2016-09-09T03:42:46Z https://api.github.com/gists/a805be84fea59cc2a... \n",
"25 2016-08-17T01:03:28Z https://api.github.com/gists/f1a5aac1f45cce380... \n",
"26 2017-09-25T23:58:13Z https://api.github.com/gists/fb76acb246c2507c2... \n",
"27 2016-09-03T16:31:02Z https://api.github.com/gists/3470c509ffa430c95... \n",
"28 2016-06-29T20:18:11Z https://api.github.com/gists/dc5b4b48af6c44f59... \n",
"29 2016-06-28T20:12:54Z https://api.github.com/gists/8acf4342c89359b31... \n",
"\n",
" user \n",
"0 None \n",
"1 None \n",
"2 None \n",
"3 None \n",
"4 None \n",
"5 None \n",
"6 None \n",
"7 None \n",
"8 None \n",
"9 None \n",
"10 None \n",
"11 None \n",
"12 None \n",
"13 None \n",
"14 None \n",
"15 None \n",
"16 None \n",
"17 None \n",
"18 None \n",
"19 None \n",
"20 None \n",
"21 None \n",
"22 None \n",
"23 None \n",
"24 None \n",
"25 None \n",
"26 None \n",
"27 None \n",
"28 None \n",
"29 None "
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Import all Gists from a Github users account\n",
"\n",
"import subprocess\n",
"import sys\n",
"import pandas as pd\n",
"import json \n",
"\n",
"if sys.version_info[0] < 3: \n",
" from StringIO import StringIO\n",
"else:\n",
" from io import StringIO\n",
"\n",
"# Used for both public and private\n",
"username = input(\"Username:\") \n",
"# Use password if you want both private and public gists, otherwise use \"\".\n",
"password = input(\"Password (blank for public only):\") \n",
"\n",
" \n",
"proc = subprocess.Popen([\"curl\", \"--user\", username + \":\" + \n",
" password, \"https://api.github.com/users/\" + username + \"/gists\"], \n",
" stdout = subprocess.PIPE)\n",
" \n",
"output = StringIO(proc.communicate()[0].decode('utf-8'))\n",
"# print(output.getvalue())\n",
"\n",
"# Convert json to dataframe\n",
"data = pd.DataFrame(json.loads(output.getvalue()))\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Search terms:py\n",
"Multiple ETF/ETN Tickers and Stats in Python\n",
"Download multiple stocks with Python Pandas\n",
"Automatic GPUs: A reproducible R / Python approach to getting up and running quickly on GCloud with GPUs in Tensorflow\n",
"GCP/GCloud VM setup running R/Python using Anaconda\n",
"Py: Adjust Splits and Dividends from Real Prices using Quandl Finance Data\n",
"Download all files within directory tree in Python\n",
"Python Download CSV from Gist (MTCARS DataSet)\n",
"Python working directory management \n",
"[Python 3] In-Memory XLS Yahoo Finance Stock Downloader Function\n",
"Python XLS In-Memory Downloader \n"
]
},
{
"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>description</th>\n",
" <th>files</th>\n",
" <th>url</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Multiple ETF/ETN Tickers and Stats in Python</td>\n",
" <td>{'etfStats.ipynb': {'filename': 'etfStats.ipyn...</td>\n",
" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Download multiple stocks with Python Pandas</td>\n",
" <td>{'multipleStocks.py': {'filename': 'multipleSt...</td>\n",
" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Automatic GPUs: A reproducible R / Python appr...</td>\n",
" <td>{'RandPythonCondaGPU.txt': {'filename': 'RandP...</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>GCP/GCloud VM setup running R/Python using Ana...</td>\n",
" <td>{'condaRandPython.txt': {'filename': 'condaRan...</td>\n",
" <td>https://api.github.com/gists/de42e70660e54f346...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Py: Adjust Splits and Dividends from Real Pric...</td>\n",
" <td>{'pythonActualPrice.ipynb': {'filename': 'pyth...</td>\n",
" <td>https://api.github.com/gists/c49ccc07af115e3de...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Download all files within directory tree in Py...</td>\n",
" <td>{'downloadTree.md': {'filename': 'downloadTree...</td>\n",
" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Python Download CSV from Gist (MTCARS DataSet)</td>\n",
" <td>{'readCsvPython.md': {'filename': 'readCsvPyth...</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Python working directory management</td>\n",
" <td>{'workingDirPython.md': {'filename': 'workingD...</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>[Python 3] In-Memory XLS Yahoo Finance Stock D...</td>\n",
" <td>{'XLSDownloader.ipynb': {'filename': 'XLSDownl...</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Python XLS In-Memory Downloader</td>\n",
" <td>{'XLSinMemory.py': {'filename': 'XLSinMemory.p...</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" description \\\n",
"1 Multiple ETF/ETN Tickers and Stats in Python \n",
"2 Download multiple stocks with Python Pandas \n",
"3 Automatic GPUs: A reproducible R / Python appr... \n",
"4 GCP/GCloud VM setup running R/Python using Ana... \n",
"5 Py: Adjust Splits and Dividends from Real Pric... \n",
"6 Download all files within directory tree in Py... \n",
"13 Python Download CSV from Gist (MTCARS DataSet) \n",
"26 Python working directory management \n",
"28 [Python 3] In-Memory XLS Yahoo Finance Stock D... \n",
"29 Python XLS In-Memory Downloader \n",
"\n",
" files \\\n",
"1 {'etfStats.ipynb': {'filename': 'etfStats.ipyn... \n",
"2 {'multipleStocks.py': {'filename': 'multipleSt... \n",
"3 {'RandPythonCondaGPU.txt': {'filename': 'RandP... \n",
"4 {'condaRandPython.txt': {'filename': 'condaRan... \n",
"5 {'pythonActualPrice.ipynb': {'filename': 'pyth... \n",
"6 {'downloadTree.md': {'filename': 'downloadTree... \n",
"13 {'readCsvPython.md': {'filename': 'readCsvPyth... \n",
"26 {'workingDirPython.md': {'filename': 'workingD... \n",
"28 {'XLSDownloader.ipynb': {'filename': 'XLSDownl... \n",
"29 {'XLSinMemory.py': {'filename': 'XLSinMemory.p... \n",
"\n",
" url \n",
"1 https://api.github.com/gists/61ad4aae5324e45c6... \n",
"2 https://api.github.com/gists/9d4946bf1fe07c27c... \n",
"3 https://api.github.com/gists/3e4ebfbd3c42edc62... \n",
"4 https://api.github.com/gists/de42e70660e54f346... \n",
"5 https://api.github.com/gists/c49ccc07af115e3de... \n",
"6 https://api.github.com/gists/61b73077d780a56d4... \n",
"13 https://api.github.com/gists/4e06d2575eb9589db... \n",
"26 https://api.github.com/gists/fb76acb246c2507c2... \n",
"28 https://api.github.com/gists/dc5b4b48af6c44f59... \n",
"29 https://api.github.com/gists/8acf4342c89359b31... "
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Filter gists by terms\n",
"import numpy as np\n",
"\n",
"text = input(\"Search terms:\").lower()\n",
"searchfor = text.split()\n",
"filteredData = data[data.description.str.lower()\n",
" .str.contains('|'.join(searchfor))][['description','files','url']]\n",
"for i in filteredData.description:\n",
" print(i)\n",
"filteredData"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'multipleStocks.py': {'filename': 'multipleStocks.py',\n",
" 'language': 'Python',\n",
" 'raw_url': 'https://gist.githubusercontent.com/ZeccaLehn/9d4946bf1fe07c27c3ad10ef83093413/raw/f2d6f8c1c183a8c676cb2f797f3482c7989fce0e/multipleStocks.py',\n",
" 'size': 2727,\n",
" 'type': 'application/x-python'}}"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filteredData.files[2] # Example we'll use is nested dict"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Choose index # from Above:2\n",
"https://gist.githubusercontent.com/ZeccaLehn/9d4946bf1fe07c27c3ad10ef83093413/raw/f2d6f8c1c183a8c676cb2f797f3482c7989fce0e/multipleStocks.py\n"
]
}
],
"source": [
"## Input index of filtered gists from table above\n",
"indexNum = int(input(\"Choose index # from Above:\"))\n",
"filteredFiles = list(filteredData[filteredData.index == indexNum].files)[0]\n",
"keys = list(filteredFiles.keys())\n",
"\n",
"## Print each sub gist\n",
"for key in keys:\n",
" print(filteredFiles[key]['raw_url']) "
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
"[*********************100%***********************] 1 of 1 downloaded\n",
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" <th></th>\n",
" <th>AKAM</th>\n",
" <th>BCOR</th>\n",
" <th>JRJC</th>\n",
" <th>CCOI</th>\n",
" <th>IAC</th>\n",
" <th>IIJI</th>\n",
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" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <tr>\n",
" <th>2005-01-03</th>\n",
" <td>12.820000</td>\n",
" <td>17.312647</td>\n",
" <td>10.49</td>\n",
" <td>17.253378</td>\n",
" <td>23.502281</td>\n",
" <td>4.164454</td>\n",
" <td>14.314034</td>\n",
" <td>11.737525</td>\n",
" <td>3.077893</td>\n",
" <td>5.728200</td>\n",
" <td>32.110001</td>\n",
" <td>2.880000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-04</th>\n",
" <td>12.200000</td>\n",
" <td>16.270340</td>\n",
" <td>10.22</td>\n",
" <td>15.655844</td>\n",
" <td>23.043747</td>\n",
" <td>3.774590</td>\n",
" <td>13.822639</td>\n",
" <td>11.601047</td>\n",
" <td>3.065631</td>\n",
" <td>5.408923</td>\n",
" <td>30.500000</td>\n",
" <td>3.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-05</th>\n",
" <td>12.000000</td>\n",
" <td>16.355350</td>\n",
" <td>10.48</td>\n",
" <td>16.774117</td>\n",
" <td>22.863928</td>\n",
" <td>3.703705</td>\n",
" <td>13.293117</td>\n",
" <td>11.466800</td>\n",
" <td>2.801987</td>\n",
" <td>5.305628</td>\n",
" <td>30.389999</td>\n",
" <td>3.560000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-06</th>\n",
" <td>11.940000</td>\n",
" <td>15.956167</td>\n",
" <td>10.26</td>\n",
" <td>15.655844</td>\n",
" <td>22.800991</td>\n",
" <td>3.650542</td>\n",
" <td>13.043181</td>\n",
" <td>11.607756</td>\n",
" <td>2.844906</td>\n",
" <td>5.183551</td>\n",
" <td>30.299999</td>\n",
" <td>3.360000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-07</th>\n",
" <td>12.150000</td>\n",
" <td>15.479369</td>\n",
" <td>9.86</td>\n",
" <td>14.537570</td>\n",
" <td>23.025764</td>\n",
" <td>3.597378</td>\n",
" <td>12.886439</td>\n",
" <td>11.618947</td>\n",
" <td>2.746805</td>\n",
" <td>5.192941</td>\n",
" <td>30.450001</td>\n",
" <td>3.480000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-10</th>\n",
" <td>12.130000</td>\n",
" <td>15.224336</td>\n",
" <td>9.65</td>\n",
" <td>14.697324</td>\n",
" <td>23.070723</td>\n",
" <td>3.358145</td>\n",
" <td>13.009291</td>\n",
" <td>11.601047</td>\n",
" <td>2.740674</td>\n",
" <td>5.305628</td>\n",
" <td>30.049999</td>\n",
" <td>4.680000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-11</th>\n",
" <td>11.670000</td>\n",
" <td>14.400101</td>\n",
" <td>9.16</td>\n",
" <td>13.738801</td>\n",
" <td>22.872919</td>\n",
" <td>3.056886</td>\n",
" <td>13.106724</td>\n",
" <td>11.180408</td>\n",
" <td>2.710018</td>\n",
" <td>5.108427</td>\n",
" <td>29.500000</td>\n",
" <td>4.520000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-12</th>\n",
" <td>12.080000</td>\n",
" <td>14.862116</td>\n",
" <td>9.10</td>\n",
" <td>12.780281</td>\n",
" <td>23.358429</td>\n",
" <td>3.242958</td>\n",
" <td>13.543049</td>\n",
" <td>11.187121</td>\n",
" <td>2.734543</td>\n",
" <td>5.070864</td>\n",
" <td>30.379999</td>\n",
" <td>4.080000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-13</th>\n",
" <td>12.260000</td>\n",
" <td>14.684701</td>\n",
" <td>8.96</td>\n",
" <td>11.821762</td>\n",
" <td>22.513281</td>\n",
" <td>3.110049</td>\n",
" <td>13.915833</td>\n",
" <td>11.377302</td>\n",
" <td>2.728412</td>\n",
" <td>5.211722</td>\n",
" <td>29.580000</td>\n",
" <td>4.480000</td>\n",
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" <tr>\n",
" <th>2005-01-14</th>\n",
" <td>12.540000</td>\n",
" <td>14.969303</td>\n",
" <td>9.10</td>\n",
" <td>11.342498</td>\n",
" <td>22.594202</td>\n",
" <td>3.260678</td>\n",
" <td>14.216604</td>\n",
" <td>11.448901</td>\n",
" <td>2.777462</td>\n",
" <td>5.221113</td>\n",
" <td>30.000000</td>\n",
" <td>4.920000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-18</th>\n",
" <td>12.860000</td>\n",
" <td>15.009961</td>\n",
" <td>9.20</td>\n",
" <td>12.460775</td>\n",
" <td>22.396400</td>\n",
" <td>3.544215</td>\n",
" <td>14.144588</td>\n",
" <td>11.417577</td>\n",
" <td>2.851037</td>\n",
" <td>5.145989</td>\n",
" <td>29.730000</td>\n",
" <td>4.680000</td>\n",
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" <tr>\n",
" <th>2005-01-19</th>\n",
" <td>12.250000</td>\n",
" <td>14.899078</td>\n",
" <td>9.15</td>\n",
" <td>12.940035</td>\n",
" <td>22.036760</td>\n",
" <td>3.588519</td>\n",
" <td>13.996322</td>\n",
" <td>11.294518</td>\n",
" <td>2.777462</td>\n",
" <td>4.911227</td>\n",
" <td>28.389999</td>\n",
" <td>4.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-20</th>\n",
" <td>12.310000</td>\n",
" <td>14.159853</td>\n",
" <td>8.75</td>\n",
" <td>12.301021</td>\n",
" <td>21.695107</td>\n",
" <td>3.508774</td>\n",
" <td>13.479506</td>\n",
" <td>10.659090</td>\n",
" <td>2.759068</td>\n",
" <td>4.789150</td>\n",
" <td>26.770000</td>\n",
" <td>4.680000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-21</th>\n",
" <td>12.200000</td>\n",
" <td>14.204206</td>\n",
" <td>8.51</td>\n",
" <td>13.259542</td>\n",
" <td>21.056751</td>\n",
" <td>3.615099</td>\n",
" <td>13.509159</td>\n",
" <td>10.077360</td>\n",
" <td>2.734543</td>\n",
" <td>4.695246</td>\n",
" <td>25.570000</td>\n",
" <td>4.720000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-24</th>\n",
" <td>12.120000</td>\n",
" <td>13.557384</td>\n",
" <td>8.17</td>\n",
" <td>13.419293</td>\n",
" <td>20.813993</td>\n",
" <td>3.561937</td>\n",
" <td>13.250751</td>\n",
" <td>9.558278</td>\n",
" <td>2.660968</td>\n",
" <td>4.544998</td>\n",
" <td>25.410000</td>\n",
" <td>4.160000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-25</th>\n",
" <td>12.260000</td>\n",
" <td>13.775455</td>\n",
" <td>8.50</td>\n",
" <td>12.940035</td>\n",
" <td>21.101706</td>\n",
" <td>3.721426</td>\n",
" <td>13.157557</td>\n",
" <td>9.925215</td>\n",
" <td>2.722281</td>\n",
" <td>4.657683</td>\n",
" <td>26.120001</td>\n",
" <td>4.120000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-26</th>\n",
" <td>12.770000</td>\n",
" <td>17.297861</td>\n",
" <td>8.48</td>\n",
" <td>13.099789</td>\n",
" <td>21.236568</td>\n",
" <td>3.898639</td>\n",
" <td>13.670135</td>\n",
" <td>9.965486</td>\n",
" <td>2.783594</td>\n",
" <td>4.920617</td>\n",
" <td>27.340000</td>\n",
" <td>3.840000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-27</th>\n",
" <td>12.660000</td>\n",
" <td>17.445707</td>\n",
" <td>9.40</td>\n",
" <td>13.259542</td>\n",
" <td>20.957850</td>\n",
" <td>3.774590</td>\n",
" <td>13.674368</td>\n",
" <td>9.723847</td>\n",
" <td>2.924612</td>\n",
" <td>4.695246</td>\n",
" <td>26.650000</td>\n",
" <td>4.320000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-28</th>\n",
" <td>12.690000</td>\n",
" <td>17.353304</td>\n",
" <td>10.28</td>\n",
" <td>12.141267</td>\n",
" <td>21.317488</td>\n",
" <td>3.739148</td>\n",
" <td>13.293117</td>\n",
" <td>9.215950</td>\n",
" <td>2.973662</td>\n",
" <td>4.554388</td>\n",
" <td>25.049999</td>\n",
" <td>4.200000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-01-31</th>\n",
" <td>13.100000</td>\n",
" <td>17.449404</td>\n",
" <td>10.27</td>\n",
" <td>9.744963</td>\n",
" <td>21.785015</td>\n",
" <td>4.075847</td>\n",
" <td>13.759095</td>\n",
" <td>9.430744</td>\n",
" <td>2.961400</td>\n",
" <td>4.657683</td>\n",
" <td>26.500000</td>\n",
" <td>4.040000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-01</th>\n",
" <td>13.080000</td>\n",
" <td>17.271988</td>\n",
" <td>9.75</td>\n",
" <td>10.224222</td>\n",
" <td>21.776031</td>\n",
" <td>4.253058</td>\n",
" <td>13.937013</td>\n",
" <td>9.446407</td>\n",
" <td>2.832643</td>\n",
" <td>4.695246</td>\n",
" <td>26.219999</td>\n",
" <td>4.040000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-02</th>\n",
" <td>12.990000</td>\n",
" <td>17.101969</td>\n",
" <td>9.54</td>\n",
" <td>10.543730</td>\n",
" <td>21.677126</td>\n",
" <td>4.164454</td>\n",
" <td>14.102220</td>\n",
" <td>9.746221</td>\n",
" <td>2.795855</td>\n",
" <td>4.676465</td>\n",
" <td>26.980000</td>\n",
" <td>4.120000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-03</th>\n",
" <td>12.760000</td>\n",
" <td>16.724962</td>\n",
" <td>9.28</td>\n",
" <td>10.863238</td>\n",
" <td>21.578226</td>\n",
" <td>4.217618</td>\n",
" <td>14.398757</td>\n",
" <td>9.788733</td>\n",
" <td>2.765199</td>\n",
" <td>4.638903</td>\n",
" <td>26.950001</td>\n",
" <td>4.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-04</th>\n",
" <td>12.080000</td>\n",
" <td>16.639952</td>\n",
" <td>9.49</td>\n",
" <td>10.383980</td>\n",
" <td>21.955847</td>\n",
" <td>4.385967</td>\n",
" <td>15.165505</td>\n",
" <td>9.730558</td>\n",
" <td>2.789724</td>\n",
" <td>4.629511</td>\n",
" <td>27.400000</td>\n",
" <td>4.520000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-07</th>\n",
" <td>11.890000</td>\n",
" <td>16.492107</td>\n",
" <td>9.34</td>\n",
" <td>10.863238</td>\n",
" <td>21.713087</td>\n",
" <td>4.554317</td>\n",
" <td>15.534053</td>\n",
" <td>9.323347</td>\n",
" <td>2.752936</td>\n",
" <td>4.620122</td>\n",
" <td>27.350000</td>\n",
" <td>4.480000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-08</th>\n",
" <td>11.750000</td>\n",
" <td>16.407095</td>\n",
" <td>9.08</td>\n",
" <td>11.182745</td>\n",
" <td>21.731075</td>\n",
" <td>4.102429</td>\n",
" <td>15.656896</td>\n",
" <td>9.224901</td>\n",
" <td>2.759068</td>\n",
" <td>4.629511</td>\n",
" <td>24.389999</td>\n",
" <td>4.440000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-09</th>\n",
" <td>11.470000</td>\n",
" <td>16.100317</td>\n",
" <td>9.25</td>\n",
" <td>12.620527</td>\n",
" <td>21.470333</td>\n",
" <td>4.510014</td>\n",
" <td>15.423914</td>\n",
" <td>8.846774</td>\n",
" <td>2.759068</td>\n",
" <td>4.620122</td>\n",
" <td>23.129999</td>\n",
" <td>4.320000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-10</th>\n",
" <td>11.230000</td>\n",
" <td>15.531115</td>\n",
" <td>9.32</td>\n",
" <td>11.502253</td>\n",
" <td>21.317488</td>\n",
" <td>4.394827</td>\n",
" <td>15.262938</td>\n",
" <td>8.703581</td>\n",
" <td>2.710018</td>\n",
" <td>4.526217</td>\n",
" <td>23.030001</td>\n",
" <td>4.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-11</th>\n",
" <td>11.400000</td>\n",
" <td>15.933992</td>\n",
" <td>7.19</td>\n",
" <td>11.502253</td>\n",
" <td>21.623180</td>\n",
" <td>4.164454</td>\n",
" <td>15.623013</td>\n",
" <td>8.665545</td>\n",
" <td>2.930744</td>\n",
" <td>4.404140</td>\n",
" <td>23.230000</td>\n",
" <td>4.040000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005-02-14</th>\n",
" <td>11.420000</td>\n",
" <td>15.985737</td>\n",
" <td>6.80</td>\n",
" <td>12.620527</td>\n",
" <td>21.335472</td>\n",
" <td>4.058127</td>\n",
" <td>15.978847</td>\n",
" <td>8.963124</td>\n",
" <td>2.881693</td>\n",
" <td>4.375968</td>\n",
" <td>23.670000</td>\n",
" <td>4.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-18</th>\n",
" <td>59.250000</td>\n",
" <td>10.540000</td>\n",
" <td>3.91</td>\n",
" <td>29.151958</td>\n",
" <td>62.200001</td>\n",
" <td>8.736260</td>\n",
" <td>76.120605</td>\n",
" <td>147.894867</td>\n",
" <td>18.624584</td>\n",
" <td>1.138496</td>\n",
" <td>50.360001</td>\n",
" <td>24.360001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-19</th>\n",
" <td>59.209999</td>\n",
" <td>10.350000</td>\n",
" <td>3.84</td>\n",
" <td>29.381081</td>\n",
" <td>62.259998</td>\n",
" <td>8.716867</td>\n",
" <td>75.988815</td>\n",
" <td>152.640350</td>\n",
" <td>18.587130</td>\n",
" <td>1.138496</td>\n",
" <td>51.709999</td>\n",
" <td>24.459999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-20</th>\n",
" <td>56.919998</td>\n",
" <td>10.110000</td>\n",
" <td>3.90</td>\n",
" <td>29.733589</td>\n",
" <td>63.939999</td>\n",
" <td>8.823526</td>\n",
" <td>76.544228</td>\n",
" <td>156.916000</td>\n",
" <td>18.718224</td>\n",
" <td>1.128929</td>\n",
" <td>51.540001</td>\n",
" <td>24.379999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-23</th>\n",
" <td>56.950001</td>\n",
" <td>10.040000</td>\n",
" <td>3.94</td>\n",
" <td>29.724775</td>\n",
" <td>62.980000</td>\n",
" <td>8.813830</td>\n",
" <td>76.214737</td>\n",
" <td>158.056839</td>\n",
" <td>18.643314</td>\n",
" <td>1.138496</td>\n",
" <td>49.750000</td>\n",
" <td>23.959999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-24</th>\n",
" <td>56.619999</td>\n",
" <td>10.180000</td>\n",
" <td>3.96</td>\n",
" <td>28.914017</td>\n",
" <td>63.230000</td>\n",
" <td>8.813830</td>\n",
" <td>75.320419</td>\n",
" <td>158.701324</td>\n",
" <td>18.746317</td>\n",
" <td>1.138496</td>\n",
" <td>50.369999</td>\n",
" <td>23.559999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-25</th>\n",
" <td>57.680000</td>\n",
" <td>10.470000</td>\n",
" <td>4.00</td>\n",
" <td>29.372272</td>\n",
" <td>63.189999</td>\n",
" <td>9.085322</td>\n",
" <td>75.649910</td>\n",
" <td>162.981964</td>\n",
" <td>18.980413</td>\n",
" <td>1.128929</td>\n",
" <td>51.009998</td>\n",
" <td>24.410000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-27</th>\n",
" <td>57.900002</td>\n",
" <td>10.290000</td>\n",
" <td>4.13</td>\n",
" <td>29.442774</td>\n",
" <td>62.930000</td>\n",
" <td>8.726563</td>\n",
" <td>75.998222</td>\n",
" <td>157.768234</td>\n",
" <td>19.158319</td>\n",
" <td>1.119361</td>\n",
" <td>49.549999</td>\n",
" <td>24.379999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-11-30</th>\n",
" <td>57.610001</td>\n",
" <td>10.630000</td>\n",
" <td>4.19</td>\n",
" <td>29.574959</td>\n",
" <td>62.790001</td>\n",
" <td>9.036843</td>\n",
" <td>75.753456</td>\n",
" <td>160.317398</td>\n",
" <td>19.111507</td>\n",
" <td>1.119361</td>\n",
" <td>50.570000</td>\n",
" <td>23.840000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-01</th>\n",
" <td>57.660000</td>\n",
" <td>10.580000</td>\n",
" <td>4.46</td>\n",
" <td>29.601397</td>\n",
" <td>62.459999</td>\n",
" <td>9.036843</td>\n",
" <td>76.026459</td>\n",
" <td>158.181885</td>\n",
" <td>19.401781</td>\n",
" <td>1.081093</td>\n",
" <td>51.799999</td>\n",
" <td>23.830000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-02</th>\n",
" <td>56.070000</td>\n",
" <td>10.460000</td>\n",
" <td>4.32</td>\n",
" <td>29.768829</td>\n",
" <td>62.660000</td>\n",
" <td>9.036843</td>\n",
" <td>75.320419</td>\n",
" <td>164.415237</td>\n",
" <td>19.317509</td>\n",
" <td>1.090660</td>\n",
" <td>51.490002</td>\n",
" <td>24.320000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-03</th>\n",
" <td>54.810001</td>\n",
" <td>10.310000</td>\n",
" <td>4.23</td>\n",
" <td>29.989151</td>\n",
" <td>60.840000</td>\n",
" <td>9.182284</td>\n",
" <td>75.423973</td>\n",
" <td>163.799622</td>\n",
" <td>19.130234</td>\n",
" <td>1.109794</td>\n",
" <td>49.680000</td>\n",
" <td>23.540001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-04</th>\n",
" <td>56.619999</td>\n",
" <td>10.360000</td>\n",
" <td>4.31</td>\n",
" <td>29.733589</td>\n",
" <td>61.330002</td>\n",
" <td>9.385905</td>\n",
" <td>76.158257</td>\n",
" <td>172.322433</td>\n",
" <td>19.476696</td>\n",
" <td>1.081093</td>\n",
" <td>51.279999</td>\n",
" <td>23.950001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-07</th>\n",
" <td>55.709999</td>\n",
" <td>10.070000</td>\n",
" <td>4.31</td>\n",
" <td>29.689522</td>\n",
" <td>60.669998</td>\n",
" <td>9.531347</td>\n",
" <td>75.725220</td>\n",
" <td>171.168106</td>\n",
" <td>19.102139</td>\n",
" <td>1.023690</td>\n",
" <td>51.230000</td>\n",
" <td>23.520000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-08</th>\n",
" <td>55.099998</td>\n",
" <td>10.080000</td>\n",
" <td>4.39</td>\n",
" <td>29.830524</td>\n",
" <td>60.439999</td>\n",
" <td>9.618614</td>\n",
" <td>75.009781</td>\n",
" <td>173.640289</td>\n",
" <td>18.989775</td>\n",
" <td>1.004555</td>\n",
" <td>50.779999</td>\n",
" <td>23.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-09</th>\n",
" <td>53.270000</td>\n",
" <td>9.830000</td>\n",
" <td>4.69</td>\n",
" <td>29.768829</td>\n",
" <td>59.389999</td>\n",
" <td>9.473171</td>\n",
" <td>74.162514</td>\n",
" <td>169.782898</td>\n",
" <td>18.708860</td>\n",
" <td>1.023690</td>\n",
" <td>49.970001</td>\n",
" <td>23.820000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-10</th>\n",
" <td>53.700001</td>\n",
" <td>10.010000</td>\n",
" <td>4.40</td>\n",
" <td>29.557331</td>\n",
" <td>59.400002</td>\n",
" <td>9.802841</td>\n",
" <td>75.546356</td>\n",
" <td>170.427429</td>\n",
" <td>18.662043</td>\n",
" <td>1.004555</td>\n",
" <td>47.770000</td>\n",
" <td>23.320000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-11</th>\n",
" <td>51.810001</td>\n",
" <td>9.550000</td>\n",
" <td>4.22</td>\n",
" <td>28.755386</td>\n",
" <td>59.669998</td>\n",
" <td>9.667093</td>\n",
" <td>72.948143</td>\n",
" <td>165.964020</td>\n",
" <td>18.231310</td>\n",
" <td>1.004555</td>\n",
" <td>46.139999</td>\n",
" <td>21.799999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-14</th>\n",
" <td>51.080002</td>\n",
" <td>10.420000</td>\n",
" <td>4.31</td>\n",
" <td>28.808262</td>\n",
" <td>60.009998</td>\n",
" <td>9.550739</td>\n",
" <td>73.126984</td>\n",
" <td>170.821808</td>\n",
" <td>18.353037</td>\n",
" <td>1.004555</td>\n",
" <td>46.939999</td>\n",
" <td>22.150000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-15</th>\n",
" <td>51.759998</td>\n",
" <td>10.360000</td>\n",
" <td>4.56</td>\n",
" <td>29.495649</td>\n",
" <td>61.070000</td>\n",
" <td>9.977372</td>\n",
" <td>72.759842</td>\n",
" <td>173.794205</td>\n",
" <td>18.671406</td>\n",
" <td>0.966286</td>\n",
" <td>48.410000</td>\n",
" <td>21.770000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-16</th>\n",
" <td>53.279999</td>\n",
" <td>10.620000</td>\n",
" <td>6.30</td>\n",
" <td>30.006771</td>\n",
" <td>62.439999</td>\n",
" <td>9.967677</td>\n",
" <td>73.061096</td>\n",
" <td>177.324539</td>\n",
" <td>19.064688</td>\n",
" <td>0.975854</td>\n",
" <td>48.779999</td>\n",
" <td>21.840000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-17</th>\n",
" <td>52.590000</td>\n",
" <td>10.670000</td>\n",
" <td>6.05</td>\n",
" <td>29.953901</td>\n",
" <td>61.520000</td>\n",
" <td>9.395599</td>\n",
" <td>72.533913</td>\n",
" <td>175.419907</td>\n",
" <td>18.755680</td>\n",
" <td>1.004555</td>\n",
" <td>49.209999</td>\n",
" <td>21.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-18</th>\n",
" <td>52.320000</td>\n",
" <td>10.170000</td>\n",
" <td>6.31</td>\n",
" <td>29.178396</td>\n",
" <td>60.169998</td>\n",
" <td>9.395599</td>\n",
" <td>72.336220</td>\n",
" <td>174.890808</td>\n",
" <td>18.568403</td>\n",
" <td>1.004555</td>\n",
" <td>49.750000</td>\n",
" <td>20.520000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-21</th>\n",
" <td>52.680000</td>\n",
" <td>10.090000</td>\n",
" <td>6.37</td>\n",
" <td>29.760023</td>\n",
" <td>60.509998</td>\n",
" <td>9.686487</td>\n",
" <td>74.190742</td>\n",
" <td>173.149734</td>\n",
" <td>18.577770</td>\n",
" <td>0.956719</td>\n",
" <td>50.770000</td>\n",
" <td>20.270000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-22</th>\n",
" <td>52.980000</td>\n",
" <td>10.240000</td>\n",
" <td>6.40</td>\n",
" <td>30.288773</td>\n",
" <td>61.250000</td>\n",
" <td>9.550739</td>\n",
" <td>75.348656</td>\n",
" <td>174.515640</td>\n",
" <td>18.699497</td>\n",
" <td>0.966286</td>\n",
" <td>50.599998</td>\n",
" <td>21.799999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-23</th>\n",
" <td>53.250000</td>\n",
" <td>10.160000</td>\n",
" <td>6.60</td>\n",
" <td>31.117163</td>\n",
" <td>61.320000</td>\n",
" <td>9.541044</td>\n",
" <td>76.205315</td>\n",
" <td>175.189011</td>\n",
" <td>18.774410</td>\n",
" <td>0.975854</td>\n",
" <td>50.779999</td>\n",
" <td>21.490000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-24</th>\n",
" <td>53.040001</td>\n",
" <td>10.400000</td>\n",
" <td>6.77</td>\n",
" <td>31.108339</td>\n",
" <td>61.639999</td>\n",
" <td>9.502260</td>\n",
" <td>76.393608</td>\n",
" <td>176.853195</td>\n",
" <td>18.802500</td>\n",
" <td>0.975854</td>\n",
" <td>50.759998</td>\n",
" <td>21.850000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-28</th>\n",
" <td>53.180000</td>\n",
" <td>10.140000</td>\n",
" <td>6.81</td>\n",
" <td>30.755842</td>\n",
" <td>60.529999</td>\n",
" <td>9.628309</td>\n",
" <td>77.579758</td>\n",
" <td>174.813873</td>\n",
" <td>18.896133</td>\n",
" <td>0.975854</td>\n",
" <td>49.779999</td>\n",
" <td>21.490000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-29</th>\n",
" <td>53.330002</td>\n",
" <td>10.080000</td>\n",
" <td>6.36</td>\n",
" <td>31.152405</td>\n",
" <td>61.000000</td>\n",
" <td>9.667093</td>\n",
" <td>78.765892</td>\n",
" <td>177.699692</td>\n",
" <td>19.130234</td>\n",
" <td>0.956719</td>\n",
" <td>50.099998</td>\n",
" <td>22.110001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-30</th>\n",
" <td>52.900002</td>\n",
" <td>10.020000</td>\n",
" <td>6.21</td>\n",
" <td>30.667717</td>\n",
" <td>60.660000</td>\n",
" <td>9.453778</td>\n",
" <td>78.596451</td>\n",
" <td>173.774963</td>\n",
" <td>18.839954</td>\n",
" <td>0.937585</td>\n",
" <td>49.310001</td>\n",
" <td>21.480000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-12-31</th>\n",
" <td>52.630001</td>\n",
" <td>9.800000</td>\n",
" <td>6.21</td>\n",
" <td>30.570782</td>\n",
" <td>60.049999</td>\n",
" <td>9.599220</td>\n",
" <td>77.495018</td>\n",
" <td>174.342499</td>\n",
" <td>18.427950</td>\n",
" <td>0.947152</td>\n",
" <td>49.400002</td>\n",
" <td>21.100000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2769 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" AKAM BCOR JRJC CCOI IAC IIJI \\\n",
"Date \n",
"2005-01-03 12.820000 17.312647 10.49 17.253378 23.502281 4.164454 \n",
"2005-01-04 12.200000 16.270340 10.22 15.655844 23.043747 3.774590 \n",
"2005-01-05 12.000000 16.355350 10.48 16.774117 22.863928 3.703705 \n",
"2005-01-06 11.940000 15.956167 10.26 15.655844 22.800991 3.650542 \n",
"2005-01-07 12.150000 15.479369 9.86 14.537570 23.025764 3.597378 \n",
"2005-01-10 12.130000 15.224336 9.65 14.697324 23.070723 3.358145 \n",
"2005-01-11 11.670000 14.400101 9.16 13.738801 22.872919 3.056886 \n",
"2005-01-12 12.080000 14.862116 9.10 12.780281 23.358429 3.242958 \n",
"2005-01-13 12.260000 14.684701 8.96 11.821762 22.513281 3.110049 \n",
"2005-01-14 12.540000 14.969303 9.10 11.342498 22.594202 3.260678 \n",
"2005-01-18 12.860000 15.009961 9.20 12.460775 22.396400 3.544215 \n",
"2005-01-19 12.250000 14.899078 9.15 12.940035 22.036760 3.588519 \n",
"2005-01-20 12.310000 14.159853 8.75 12.301021 21.695107 3.508774 \n",
"2005-01-21 12.200000 14.204206 8.51 13.259542 21.056751 3.615099 \n",
"2005-01-24 12.120000 13.557384 8.17 13.419293 20.813993 3.561937 \n",
"2005-01-25 12.260000 13.775455 8.50 12.940035 21.101706 3.721426 \n",
"2005-01-26 12.770000 17.297861 8.48 13.099789 21.236568 3.898639 \n",
"2005-01-27 12.660000 17.445707 9.40 13.259542 20.957850 3.774590 \n",
"2005-01-28 12.690000 17.353304 10.28 12.141267 21.317488 3.739148 \n",
"2005-01-31 13.100000 17.449404 10.27 9.744963 21.785015 4.075847 \n",
"2005-02-01 13.080000 17.271988 9.75 10.224222 21.776031 4.253058 \n",
"2005-02-02 12.990000 17.101969 9.54 10.543730 21.677126 4.164454 \n",
"2005-02-03 12.760000 16.724962 9.28 10.863238 21.578226 4.217618 \n",
"2005-02-04 12.080000 16.639952 9.49 10.383980 21.955847 4.385967 \n",
"2005-02-07 11.890000 16.492107 9.34 10.863238 21.713087 4.554317 \n",
"2005-02-08 11.750000 16.407095 9.08 11.182745 21.731075 4.102429 \n",
"2005-02-09 11.470000 16.100317 9.25 12.620527 21.470333 4.510014 \n",
"2005-02-10 11.230000 15.531115 9.32 11.502253 21.317488 4.394827 \n",
"2005-02-11 11.400000 15.933992 7.19 11.502253 21.623180 4.164454 \n",
"2005-02-14 11.420000 15.985737 6.80 12.620527 21.335472 4.058127 \n",
"... ... ... ... ... ... ... \n",
"2015-11-18 59.250000 10.540000 3.91 29.151958 62.200001 8.736260 \n",
"2015-11-19 59.209999 10.350000 3.84 29.381081 62.259998 8.716867 \n",
"2015-11-20 56.919998 10.110000 3.90 29.733589 63.939999 8.823526 \n",
"2015-11-23 56.950001 10.040000 3.94 29.724775 62.980000 8.813830 \n",
"2015-11-24 56.619999 10.180000 3.96 28.914017 63.230000 8.813830 \n",
"2015-11-25 57.680000 10.470000 4.00 29.372272 63.189999 9.085322 \n",
"2015-11-27 57.900002 10.290000 4.13 29.442774 62.930000 8.726563 \n",
"2015-11-30 57.610001 10.630000 4.19 29.574959 62.790001 9.036843 \n",
"2015-12-01 57.660000 10.580000 4.46 29.601397 62.459999 9.036843 \n",
"2015-12-02 56.070000 10.460000 4.32 29.768829 62.660000 9.036843 \n",
"2015-12-03 54.810001 10.310000 4.23 29.989151 60.840000 9.182284 \n",
"2015-12-04 56.619999 10.360000 4.31 29.733589 61.330002 9.385905 \n",
"2015-12-07 55.709999 10.070000 4.31 29.689522 60.669998 9.531347 \n",
"2015-12-08 55.099998 10.080000 4.39 29.830524 60.439999 9.618614 \n",
"2015-12-09 53.270000 9.830000 4.69 29.768829 59.389999 9.473171 \n",
"2015-12-10 53.700001 10.010000 4.40 29.557331 59.400002 9.802841 \n",
"2015-12-11 51.810001 9.550000 4.22 28.755386 59.669998 9.667093 \n",
"2015-12-14 51.080002 10.420000 4.31 28.808262 60.009998 9.550739 \n",
"2015-12-15 51.759998 10.360000 4.56 29.495649 61.070000 9.977372 \n",
"2015-12-16 53.279999 10.620000 6.30 30.006771 62.439999 9.967677 \n",
"2015-12-17 52.590000 10.670000 6.05 29.953901 61.520000 9.395599 \n",
"2015-12-18 52.320000 10.170000 6.31 29.178396 60.169998 9.395599 \n",
"2015-12-21 52.680000 10.090000 6.37 29.760023 60.509998 9.686487 \n",
"2015-12-22 52.980000 10.240000 6.40 30.288773 61.250000 9.550739 \n",
"2015-12-23 53.250000 10.160000 6.60 31.117163 61.320000 9.541044 \n",
"2015-12-24 53.040001 10.400000 6.77 31.108339 61.639999 9.502260 \n",
"2015-12-28 53.180000 10.140000 6.81 30.755842 60.529999 9.628309 \n",
"2015-12-29 53.330002 10.080000 6.36 31.152405 61.000000 9.667093 \n",
"2015-12-30 52.900002 10.020000 6.21 30.667717 60.660000 9.453778 \n",
"2015-12-31 52.630001 9.800000 6.21 30.570782 60.049999 9.599220 \n",
"\n",
" JCOM NTES EGOV SIFY SINA TCX \n",
"Date \n",
"2005-01-03 14.314034 11.737525 3.077893 5.728200 32.110001 2.880000 \n",
"2005-01-04 13.822639 11.601047 3.065631 5.408923 30.500000 3.600000 \n",
"2005-01-05 13.293117 11.466800 2.801987 5.305628 30.389999 3.560000 \n",
"2005-01-06 13.043181 11.607756 2.844906 5.183551 30.299999 3.360000 \n",
"2005-01-07 12.886439 11.618947 2.746805 5.192941 30.450001 3.480000 \n",
"2005-01-10 13.009291 11.601047 2.740674 5.305628 30.049999 4.680000 \n",
"2005-01-11 13.106724 11.180408 2.710018 5.108427 29.500000 4.520000 \n",
"2005-01-12 13.543049 11.187121 2.734543 5.070864 30.379999 4.080000 \n",
"2005-01-13 13.915833 11.377302 2.728412 5.211722 29.580000 4.480000 \n",
"2005-01-14 14.216604 11.448901 2.777462 5.221113 30.000000 4.920000 \n",
"2005-01-18 14.144588 11.417577 2.851037 5.145989 29.730000 4.680000 \n",
"2005-01-19 13.996322 11.294518 2.777462 4.911227 28.389999 4.800000 \n",
"2005-01-20 13.479506 10.659090 2.759068 4.789150 26.770000 4.680000 \n",
"2005-01-21 13.509159 10.077360 2.734543 4.695246 25.570000 4.720000 \n",
"2005-01-24 13.250751 9.558278 2.660968 4.544998 25.410000 4.160000 \n",
"2005-01-25 13.157557 9.925215 2.722281 4.657683 26.120001 4.120000 \n",
"2005-01-26 13.670135 9.965486 2.783594 4.920617 27.340000 3.840000 \n",
"2005-01-27 13.674368 9.723847 2.924612 4.695246 26.650000 4.320000 \n",
"2005-01-28 13.293117 9.215950 2.973662 4.554388 25.049999 4.200000 \n",
"2005-01-31 13.759095 9.430744 2.961400 4.657683 26.500000 4.040000 \n",
"2005-02-01 13.937013 9.446407 2.832643 4.695246 26.219999 4.040000 \n",
"2005-02-02 14.102220 9.746221 2.795855 4.676465 26.980000 4.120000 \n",
"2005-02-03 14.398757 9.788733 2.765199 4.638903 26.950001 4.400000 \n",
"2005-02-04 15.165505 9.730558 2.789724 4.629511 27.400000 4.520000 \n",
"2005-02-07 15.534053 9.323347 2.752936 4.620122 27.350000 4.480000 \n",
"2005-02-08 15.656896 9.224901 2.759068 4.629511 24.389999 4.440000 \n",
"2005-02-09 15.423914 8.846774 2.759068 4.620122 23.129999 4.320000 \n",
"2005-02-10 15.262938 8.703581 2.710018 4.526217 23.030001 4.400000 \n",
"2005-02-11 15.623013 8.665545 2.930744 4.404140 23.230000 4.040000 \n",
"2005-02-14 15.978847 8.963124 2.881693 4.375968 23.670000 4.000000 \n",
"... ... ... ... ... ... ... \n",
"2015-11-18 76.120605 147.894867 18.624584 1.138496 50.360001 24.360001 \n",
"2015-11-19 75.988815 152.640350 18.587130 1.138496 51.709999 24.459999 \n",
"2015-11-20 76.544228 156.916000 18.718224 1.128929 51.540001 24.379999 \n",
"2015-11-23 76.214737 158.056839 18.643314 1.138496 49.750000 23.959999 \n",
"2015-11-24 75.320419 158.701324 18.746317 1.138496 50.369999 23.559999 \n",
"2015-11-25 75.649910 162.981964 18.980413 1.128929 51.009998 24.410000 \n",
"2015-11-27 75.998222 157.768234 19.158319 1.119361 49.549999 24.379999 \n",
"2015-11-30 75.753456 160.317398 19.111507 1.119361 50.570000 23.840000 \n",
"2015-12-01 76.026459 158.181885 19.401781 1.081093 51.799999 23.830000 \n",
"2015-12-02 75.320419 164.415237 19.317509 1.090660 51.490002 24.320000 \n",
"2015-12-03 75.423973 163.799622 19.130234 1.109794 49.680000 23.540001 \n",
"2015-12-04 76.158257 172.322433 19.476696 1.081093 51.279999 23.950001 \n",
"2015-12-07 75.725220 171.168106 19.102139 1.023690 51.230000 23.520000 \n",
"2015-12-08 75.009781 173.640289 18.989775 1.004555 50.779999 23.500000 \n",
"2015-12-09 74.162514 169.782898 18.708860 1.023690 49.970001 23.820000 \n",
"2015-12-10 75.546356 170.427429 18.662043 1.004555 47.770000 23.320000 \n",
"2015-12-11 72.948143 165.964020 18.231310 1.004555 46.139999 21.799999 \n",
"2015-12-14 73.126984 170.821808 18.353037 1.004555 46.939999 22.150000 \n",
"2015-12-15 72.759842 173.794205 18.671406 0.966286 48.410000 21.770000 \n",
"2015-12-16 73.061096 177.324539 19.064688 0.975854 48.779999 21.840000 \n",
"2015-12-17 72.533913 175.419907 18.755680 1.004555 49.209999 21.250000 \n",
"2015-12-18 72.336220 174.890808 18.568403 1.004555 49.750000 20.520000 \n",
"2015-12-21 74.190742 173.149734 18.577770 0.956719 50.770000 20.270000 \n",
"2015-12-22 75.348656 174.515640 18.699497 0.966286 50.599998 21.799999 \n",
"2015-12-23 76.205315 175.189011 18.774410 0.975854 50.779999 21.490000 \n",
"2015-12-24 76.393608 176.853195 18.802500 0.975854 50.759998 21.850000 \n",
"2015-12-28 77.579758 174.813873 18.896133 0.975854 49.779999 21.490000 \n",
"2015-12-29 78.765892 177.699692 19.130234 0.956719 50.099998 22.110001 \n",
"2015-12-30 78.596451 173.774963 18.839954 0.937585 49.310001 21.480000 \n",
"2015-12-31 77.495018 174.342499 18.427950 0.947152 49.400002 21.100000 \n",
"\n",
"[2769 rows x 12 columns]"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Executing code directly fromm Gists\n",
"\n",
" # Confirm Jupyter Notebook uses Conda env Python version\n",
" # Install: pip install fix_yahoo_finance --upgrade --no-cache-dir\n",
" # Install: pip install git+https://github.com/pydata/pandas-datareader.git\n",
"\n",
"import requests\n",
"url = \"https://gist.githubusercontent.com/ZeccaLehn/9d4946bf1fe07c27c3ad10ef83093413/raw/f2d6f8c1c183a8c676cb2f797f3482c7989fce0e/multipleStocks.py\"\n",
"response = requests.get(url)\n",
"exec(response.text)\n",
"allData\n",
"\n",
" ## Note: For JSON Direct downloads\n",
" # proc = subprocess.Popen([\"curl\", url], stdout = subprocess.PIPE)\n",
" # output = StringIO(proc.communicate()[0].decode('utf-8'))\n",
" # output.getvalue()\n",
" # output = json.loads(output.getvalue())\n",
" # output"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"## Overview of code example\n",
"if True == False:\n",
"\n",
" # Clone and pip install pandas_datareader from Github first\n",
" # pip install git+https://github.com/pydata/pandas-datareader.git\n",
" # pip install fix_yahoo_finance --upgrade --no-cache-dir\n",
"\n",
" import pandas as pd\n",
" pd.core.common.is_list_like = pd.api.types.is_list_like\n",
" from pandas.api.types import is_list_like\n",
" from pandas_datareader import data as pdr\n",
" import fix_yahoo_finance as yf\n",
" yf.pdr_override()\n",
"\n",
" #scrape html from website and store 3rd DataFrame as our stock tickers - this is dictated to us by the structure of the html\n",
" stock_list = pd.read_html(\"https://www.marketwatch.com/tools/industry/stocklist.asp?bcind_ind=9535&amp;bcind_period=3mo\")[3]\n",
" #convert the DataFrame of stocks into a list so we can easily iterate over it\n",
" tickers = stock_list[1].dropna()[1:].tolist()\n",
"\n",
" start_date = '2005-01-01'\n",
" end_date = '2016-01-01'\n",
"\n",
" exchange = 'yahoo'\n",
" column_name = 'Adj Close' # 'Open' 'High' 'Low' 'Close' 'Adj Close' 'Volume'\n",
"\n",
"\n",
" allData = pd.DataFrame()\n",
" finalTickers = []\n",
" for ticker in tickers:\n",
" try:\n",
"\n",
" allData = pd.merge(allData, pd.DataFrame(pdr.get_data_yahoo(ticker, fields='price', \n",
" start=start_date, end=end_date)['Adj Close']), \n",
" right_index=True, left_index=True, how='outer')\n",
"\n",
" # Appends tickers which have data\n",
" finalTickers.append(ticker)\n",
"\n",
" except: \n",
" next \n",
"\n",
" allData.columns = finalTickers\n",
" allData = allData.dropna(axis='columns')\n",
" allData"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"def helloTest(param):\n",
" print(\"Hello \", param, \"!!!\")\n"
]
}
],
"source": [
"## Execute from Gist\n",
"import requests\n",
"url = \"https://gist.githubusercontent.com/ZeccaLehn/7f1a10f12989225e0ea9575793974ae5/raw/1af563d6a4598350451d9a76ea3cdf83f159f03a/helloTest.py\"\n",
"response = requests.get(url)\n",
"exec(response.text)\n",
"print(response.text)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello Everyone !!!\n"
]
}
],
"source": [
"helloTest(\"Everyone\")"
]
},
{
"cell_type": "code",
"execution_count": 44,
"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>description</th>\n",
" <th>files</th>\n",
" <th>url</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Multiple ETF/ETN Tickers and Stats in Python</td>\n",
" <td>{'etfStats.ipynb': {'filename': 'etfStats.ipyn...</td>\n",
" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Download multiple stocks with Python Pandas</td>\n",
" <td>{'multipleStocks.py': {'filename': 'multipleSt...</td>\n",
" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Automatic GPUs: A reproducible R / Python appr...</td>\n",
" <td>{'RandPythonCondaGPU.txt': {'filename': 'RandP...</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>GCP/GCloud VM setup running R/Python using Ana...</td>\n",
" <td>{'condaRandPython.txt': {'filename': 'condaRan...</td>\n",
" <td>https://api.github.com/gists/de42e70660e54f346...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Py: Adjust Splits and Dividends from Real Pric...</td>\n",
" <td>{'pythonActualPrice.ipynb': {'filename': 'pyth...</td>\n",
" <td>https://api.github.com/gists/c49ccc07af115e3de...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Download all files within directory tree in Py...</td>\n",
" <td>{'downloadTree.md': {'filename': 'downloadTree...</td>\n",
" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Python Download CSV from Gist (MTCARS DataSet)</td>\n",
" <td>{'readCsvPython.md': {'filename': 'readCsvPyth...</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Python working directory management</td>\n",
" <td>{'workingDirPython.md': {'filename': 'workingD...</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>[Python 3] In-Memory XLS Yahoo Finance Stock D...</td>\n",
" <td>{'XLSDownloader.ipynb': {'filename': 'XLSDownl...</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Python XLS In-Memory Downloader</td>\n",
" <td>{'XLSinMemory.py': {'filename': 'XLSinMemory.p...</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" description \\\n",
"1 Multiple ETF/ETN Tickers and Stats in Python \n",
"2 Download multiple stocks with Python Pandas \n",
"3 Automatic GPUs: A reproducible R / Python appr... \n",
"4 GCP/GCloud VM setup running R/Python using Ana... \n",
"5 Py: Adjust Splits and Dividends from Real Pric... \n",
"6 Download all files within directory tree in Py... \n",
"13 Python Download CSV from Gist (MTCARS DataSet) \n",
"26 Python working directory management \n",
"28 [Python 3] In-Memory XLS Yahoo Finance Stock D... \n",
"29 Python XLS In-Memory Downloader \n",
"\n",
" files \\\n",
"1 {'etfStats.ipynb': {'filename': 'etfStats.ipyn... \n",
"2 {'multipleStocks.py': {'filename': 'multipleSt... \n",
"3 {'RandPythonCondaGPU.txt': {'filename': 'RandP... \n",
"4 {'condaRandPython.txt': {'filename': 'condaRan... \n",
"5 {'pythonActualPrice.ipynb': {'filename': 'pyth... \n",
"6 {'downloadTree.md': {'filename': 'downloadTree... \n",
"13 {'readCsvPython.md': {'filename': 'readCsvPyth... \n",
"26 {'workingDirPython.md': {'filename': 'workingD... \n",
"28 {'XLSDownloader.ipynb': {'filename': 'XLSDownl... \n",
"29 {'XLSinMemory.py': {'filename': 'XLSinMemory.p... \n",
"\n",
" url \n",
"1 https://api.github.com/gists/61ad4aae5324e45c6... \n",
"2 https://api.github.com/gists/9d4946bf1fe07c27c... \n",
"3 https://api.github.com/gists/3e4ebfbd3c42edc62... \n",
"4 https://api.github.com/gists/de42e70660e54f346... \n",
"5 https://api.github.com/gists/c49ccc07af115e3de... \n",
"6 https://api.github.com/gists/61b73077d780a56d4... \n",
"13 https://api.github.com/gists/4e06d2575eb9589db... \n",
"26 https://api.github.com/gists/fb76acb246c2507c2... \n",
"28 https://api.github.com/gists/dc5b4b48af6c44f59... \n",
"29 https://api.github.com/gists/8acf4342c89359b31... "
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filteredData"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" 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>description</th>\n",
" <th>files</th>\n",
" <th>url</th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Multiple ETF/ETN Tickers and Stats in Python</td>\n",
" <td>{'etfStats.ipynb': {'filename': 'etfStats.ipyn...</td>\n",
" <td>https://api.github.com/gists/61ad4aae5324e45c6...</td>\n",
" <td>{'filename': 'etfStats.ipynb', 'type': 'text/p...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Download multiple stocks with Python Pandas</td>\n",
" <td>{'multipleStocks.py': {'filename': 'multipleSt...</td>\n",
" <td>https://api.github.com/gists/9d4946bf1fe07c27c...</td>\n",
" <td>{'filename': 'multipleStocks.py', 'type': 'app...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Automatic GPUs: A reproducible R / Python appr...</td>\n",
" <td>{'RandPythonCondaGPU.txt': {'filename': 'RandP...</td>\n",
" <td>https://api.github.com/gists/3e4ebfbd3c42edc62...</td>\n",
" <td>{'filename': 'RandPythonCondaGPU.txt', 'type':...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>GCP/GCloud VM setup running R/Python using Ana...</td>\n",
" <td>{'condaRandPython.txt': {'filename': 'condaRan...</td>\n",
" <td>https://api.github.com/gists/de42e70660e54f346...</td>\n",
" <td>{'filename': 'condaRandPython.txt', 'type': 't...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Py: Adjust Splits and Dividends from Real Pric...</td>\n",
" <td>{'pythonActualPrice.ipynb': {'filename': 'pyth...</td>\n",
" <td>https://api.github.com/gists/c49ccc07af115e3de...</td>\n",
" <td>{'filename': 'pythonActualPrice.ipynb', 'type'...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Download all files within directory tree in Py...</td>\n",
" <td>{'downloadTree.md': {'filename': 'downloadTree...</td>\n",
" <td>https://api.github.com/gists/61b73077d780a56d4...</td>\n",
" <td>{'filename': 'downloadTree.md', 'type': 'text/...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Python Download CSV from Gist (MTCARS DataSet)</td>\n",
" <td>{'readCsvPython.md': {'filename': 'readCsvPyth...</td>\n",
" <td>https://api.github.com/gists/4e06d2575eb9589db...</td>\n",
" <td>{'filename': 'mtcars.csv', 'type': 'text/csv',...</td>\n",
" <td>{'filename': 'readCsvPython.md', 'type': 'text...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Python working directory management</td>\n",
" <td>{'workingDirPython.md': {'filename': 'workingD...</td>\n",
" <td>https://api.github.com/gists/fb76acb246c2507c2...</td>\n",
" <td>{'filename': 'workingDirPython.md', 'type': 't...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>[Python 3] In-Memory XLS Yahoo Finance Stock D...</td>\n",
" <td>{'XLSDownloader.ipynb': {'filename': 'XLSDownl...</td>\n",
" <td>https://api.github.com/gists/dc5b4b48af6c44f59...</td>\n",
" <td>{'filename': 'XLSDownloader.ipynb', 'type': 't...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Python XLS In-Memory Downloader</td>\n",
" <td>{'XLSinMemory.py': {'filename': 'XLSinMemory.p...</td>\n",
" <td>https://api.github.com/gists/8acf4342c89359b31...</td>\n",
" <td>{'filename': 'XLSinMemory.py', 'type': 'applic...</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" description \\\n",
"1 Multiple ETF/ETN Tickers and Stats in Python \n",
"2 Download multiple stocks with Python Pandas \n",
"3 Automatic GPUs: A reproducible R / Python appr... \n",
"4 GCP/GCloud VM setup running R/Python using Ana... \n",
"5 Py: Adjust Splits and Dividends from Real Pric... \n",
"6 Download all files within directory tree in Py... \n",
"13 Python Download CSV from Gist (MTCARS DataSet) \n",
"26 Python working directory management \n",
"28 [Python 3] In-Memory XLS Yahoo Finance Stock D... \n",
"29 Python XLS In-Memory Downloader \n",
"\n",
" files \\\n",
"1 {'etfStats.ipynb': {'filename': 'etfStats.ipyn... \n",
"2 {'multipleStocks.py': {'filename': 'multipleSt... \n",
"3 {'RandPythonCondaGPU.txt': {'filename': 'RandP... \n",
"4 {'condaRandPython.txt': {'filename': 'condaRan... \n",
"5 {'pythonActualPrice.ipynb': {'filename': 'pyth... \n",
"6 {'downloadTree.md': {'filename': 'downloadTree... \n",
"13 {'readCsvPython.md': {'filename': 'readCsvPyth... \n",
"26 {'workingDirPython.md': {'filename': 'workingD... \n",
"28 {'XLSDownloader.ipynb': {'filename': 'XLSDownl... \n",
"29 {'XLSinMemory.py': {'filename': 'XLSinMemory.p... \n",
"\n",
" url \\\n",
"1 https://api.github.com/gists/61ad4aae5324e45c6... \n",
"2 https://api.github.com/gists/9d4946bf1fe07c27c... \n",
"3 https://api.github.com/gists/3e4ebfbd3c42edc62... \n",
"4 https://api.github.com/gists/de42e70660e54f346... \n",
"5 https://api.github.com/gists/c49ccc07af115e3de... \n",
"6 https://api.github.com/gists/61b73077d780a56d4... \n",
"13 https://api.github.com/gists/4e06d2575eb9589db... \n",
"26 https://api.github.com/gists/fb76acb246c2507c2... \n",
"28 https://api.github.com/gists/dc5b4b48af6c44f59... \n",
"29 https://api.github.com/gists/8acf4342c89359b31... \n",
"\n",
" 0 \\\n",
"1 {'filename': 'etfStats.ipynb', 'type': 'text/p... \n",
"2 {'filename': 'multipleStocks.py', 'type': 'app... \n",
"3 {'filename': 'RandPythonCondaGPU.txt', 'type':... \n",
"4 {'filename': 'condaRandPython.txt', 'type': 't... \n",
"5 {'filename': 'pythonActualPrice.ipynb', 'type'... \n",
"6 {'filename': 'downloadTree.md', 'type': 'text/... \n",
"13 {'filename': 'mtcars.csv', 'type': 'text/csv',... \n",
"26 {'filename': 'workingDirPython.md', 'type': 't... \n",
"28 {'filename': 'XLSDownloader.ipynb', 'type': 't... \n",
"29 {'filename': 'XLSinMemory.py', 'type': 'applic... \n",
"\n",
" 1 \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
"5 NaN \n",
"6 NaN \n",
"13 {'filename': 'readCsvPython.md', 'type': 'text... \n",
"26 NaN \n",
"28 NaN \n",
"29 NaN "
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## Unnest data for a complete view\n",
"from pandas.io.json import json_normalize\n",
"filterFiles = filteredData.files.apply(pd.Series).T # .iloc[0,:].dropna()\n",
"fileNames = pd.Series(list(filterFiles.index))\n",
"testData = pd.concat([pd.Series(filterFiles[c].dropna().values, name = c) for c in filterFiles], axis=1).T\n",
"testData = pd.concat([filteredData, testData], axis=1)\n",
"testData\n",
"\n",
"# json_normalize(testData.iloc[:,4])"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"pythonActualPrice.ipynb\n",
"downloadTree.md\n",
"{'filename': 'pythonActualPrice.ipynb', 'type': 'text/plain', 'raw_url': 'https://gist.githubusercontent.com/ZeccaLehn/c49ccc07af115e3dec878ed8a68b21d0/raw/5d85b0895c0c2db5906f5d52a6bef5846e2a5ec8/pythonActualPrice.ipynb', 'language': 'Jupyter Notebook', 'size': 100759}\n",
"{'filename': 'downloadTree.md', 'type': 'text/plain', 'raw_url': 'https://gist.githubusercontent.com/ZeccaLehn/61b73077d780a56d40cdda6dfe383a1a/raw/2811652224edefe9cbb415f3c7853addf01290bf/downloadTree.md', 'language': 'Markdown', 'size': 376}\n"
]
}
],
"source": [
"print(testData.iloc[:,3][5]['filename'])\n",
"print(testData.iloc[:,3][6]['filename'])\n",
"\n",
"print(testData.iloc[:,3][5])\n",
"print(testData.iloc[:,3][6])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<bound method Github.get_gist of <github.MainClass.Github object at 0x000002C0AFE8B9E8>>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"## May be possible to download all secret and public gists using this package\n",
"from github import Github\n",
"g = Github(<Your Github Key>)\n",
"\n",
"# for repo in g.get_gists():\n",
"# print(repo.name)\n",
"# print(dir(repo))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.5.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
@ZeccaLehn
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Referenced from blog post: https://medium.com/@zecca/level-up-using-gists-with-python-b393a97b6b89

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