Created
May 30, 2015 16:22
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| { | |
| "worksheets": [ | |
| { | |
| "cells": [ | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "import pandas as pd\nimport numpy as np", | |
| "prompt_number": 1, | |
| "outputs": [], | |
| "language": "python", | |
| "trusted": true, | |
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| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "df = pd.DataFrame(np.random.randn(50))", | |
| "prompt_number": 8, | |
| "outputs": [], | |
| "language": "python", | |
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| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "df.shape", | |
| "prompt_number": 14, | |
| "outputs": [ | |
| { | |
| "text": "(50, 1)", | |
| "output_type": "pyout", | |
| "metadata": {}, | |
| "prompt_number": 14 | |
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| "cell_type": "markdown", | |
| "source": "Now the question becomes, we have 50 observations and we know that those occur every 10 seconds - how do we create that range?\n\nFirstly, we need to generate the entire range from start to end.\n\nWe know that it occurs 50obs. \\* 10 seconds = 500 seconds" | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "pd.date_range(start='5-30-2015 00:00:00',periods=df.shape[0] * 10,freq='S')", | |
| "prompt_number": 70, | |
| "outputs": [ | |
| { | |
| "text": "<class 'pandas.tseries.index.DatetimeIndex'>\n[2015-05-30 00:00:00, ..., 2015-05-30 00:08:19]\nLength: 500, Freq: S, Timezone: None", | |
| "output_type": "pyout", | |
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| "prompt_number": 70 | |
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| { | |
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| "cell_type": "markdown", | |
| "source": "Set those equal" | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "ind = pd.date_range(start='5-30-2015 00:00:00',periods=df.shape[0] * 10,freq='S') # adding one to get that last second coverage", | |
| "prompt_number": 97, | |
| "outputs": [], | |
| "language": "python", | |
| "trusted": true, | |
| "collapsed": false | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "markdown", | |
| "source": "Now we need to filter to all those values that are divisible by our number, now it's occurring every 10 seconds, so essentially we need to get every date time that ends in a 0." | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "ind_df = pd.Series(ind)", | |
| "prompt_number": 106, | |
| "outputs": [], | |
| "language": "python", | |
| "trusted": true, | |
| "collapsed": false | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "filt = ind_df.map(lambda x: x.second in [x for x in range(0,60,10)])", | |
| "prompt_number": 107, | |
| "outputs": [], | |
| "language": "python", | |
| "trusted": true, | |
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| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "ind_df[filt].head(8)", | |
| "prompt_number": 108, | |
| "outputs": [ | |
| { | |
| "text": "0 2015-05-30 00:00:00\n10 2015-05-30 00:00:10\n20 2015-05-30 00:00:20\n30 2015-05-30 00:00:30\n40 2015-05-30 00:00:40\n50 2015-05-30 00:00:50\n60 2015-05-30 00:01:00\n70 2015-05-30 00:01:10\ndtype: datetime64[ns]", | |
| "output_type": "pyout", | |
| "metadata": {}, | |
| "prompt_number": 108 | |
| } | |
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| "language": "python", | |
| "trusted": true, | |
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| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "df.index = ind_df[filt]", | |
| "prompt_number": 109, | |
| "outputs": [], | |
| "language": "python", | |
| "trusted": true, | |
| "collapsed": false | |
| }, | |
| { | |
| "metadata": {}, | |
| "cell_type": "code", | |
| "input": "df['2015-05-30']", | |
| "prompt_number": 110, | |
| "outputs": [ | |
| { | |
| "text": " 0\n2015-05-30 00:00:00 -2.541960\n2015-05-30 00:00:10 1.418795\n2015-05-30 00:00:20 0.424278\n2015-05-30 00:00:30 -0.431099\n2015-05-30 00:00:40 -0.793842\n2015-05-30 00:00:50 0.868189\n2015-05-30 00:01:00 0.948918\n2015-05-30 00:01:10 0.140921\n2015-05-30 00:01:20 -1.827831\n2015-05-30 00:01:30 -1.934219\n2015-05-30 00:01:40 -0.545092\n2015-05-30 00:01:50 -0.554454\n2015-05-30 00:02:00 -0.387286\n2015-05-30 00:02:10 -2.982757\n2015-05-30 00:02:20 0.501777\n2015-05-30 00:02:30 0.552225\n2015-05-30 00:02:40 -0.659359\n2015-05-30 00:02:50 0.105699\n2015-05-30 00:03:00 -0.620858\n2015-05-30 00:03:10 0.376805\n2015-05-30 00:03:20 0.799189\n2015-05-30 00:03:30 -1.500560\n2015-05-30 00:03:40 0.454522\n2015-05-30 00:03:50 1.435372\n2015-05-30 00:04:00 -0.713203\n2015-05-30 00:04:10 0.530396\n2015-05-30 00:04:20 -1.289187\n2015-05-30 00:04:30 1.031124\n2015-05-30 00:04:40 0.664521\n2015-05-30 00:04:50 -0.364961\n2015-05-30 00:05:00 -0.162748\n2015-05-30 00:05:10 -0.258509\n2015-05-30 00:05:20 0.172308\n2015-05-30 00:05:30 0.745513\n2015-05-30 00:05:40 -0.098311\n2015-05-30 00:05:50 -1.599429\n2015-05-30 00:06:00 1.869689\n2015-05-30 00:06:10 -0.330046\n2015-05-30 00:06:20 1.295800\n2015-05-30 00:06:30 1.866889\n2015-05-30 00:06:40 -0.486605\n2015-05-30 00:06:50 2.256074\n2015-05-30 00:07:00 -1.655385\n2015-05-30 00:07:10 1.087934\n2015-05-30 00:07:20 0.107526\n2015-05-30 00:07:30 -1.509951\n2015-05-30 00:07:40 -0.798577\n2015-05-30 00:07:50 1.921219\n2015-05-30 00:08:00 -1.495371\n2015-05-30 00:08:10 0.647703", | |
| "html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>0</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>2015-05-30 00:00:00</th>\n <td>-2.541960</td>\n </tr>\n <tr>\n <th>2015-05-30 00:00:10</th>\n <td> 1.418795</td>\n </tr>\n <tr>\n <th>2015-05-30 00:00:20</th>\n <td> 0.424278</td>\n </tr>\n <tr>\n <th>2015-05-30 00:00:30</th>\n <td>-0.431099</td>\n </tr>\n <tr>\n <th>2015-05-30 00:00:40</th>\n <td>-0.793842</td>\n </tr>\n <tr>\n <th>2015-05-30 00:00:50</th>\n <td> 0.868189</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:00</th>\n <td> 0.948918</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:10</th>\n <td> 0.140921</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:20</th>\n <td>-1.827831</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:30</th>\n <td>-1.934219</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:40</th>\n <td>-0.545092</td>\n </tr>\n <tr>\n <th>2015-05-30 00:01:50</th>\n <td>-0.554454</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:00</th>\n <td>-0.387286</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:10</th>\n <td>-2.982757</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:20</th>\n <td> 0.501777</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:30</th>\n <td> 0.552225</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:40</th>\n <td>-0.659359</td>\n </tr>\n <tr>\n <th>2015-05-30 00:02:50</th>\n <td> 0.105699</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:00</th>\n <td>-0.620858</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:10</th>\n <td> 0.376805</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:20</th>\n <td> 0.799189</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:30</th>\n <td>-1.500560</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:40</th>\n <td> 0.454522</td>\n </tr>\n <tr>\n <th>2015-05-30 00:03:50</th>\n <td> 1.435372</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:00</th>\n <td>-0.713203</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:10</th>\n <td> 0.530396</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:20</th>\n <td>-1.289187</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:30</th>\n <td> 1.031124</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:40</th>\n <td> 0.664521</td>\n </tr>\n <tr>\n <th>2015-05-30 00:04:50</th>\n <td>-0.364961</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:00</th>\n <td>-0.162748</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:10</th>\n <td>-0.258509</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:20</th>\n <td> 0.172308</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:30</th>\n <td> 0.745513</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:40</th>\n <td>-0.098311</td>\n </tr>\n <tr>\n <th>2015-05-30 00:05:50</th>\n <td>-1.599429</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:00</th>\n <td> 1.869689</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:10</th>\n <td>-0.330046</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:20</th>\n <td> 1.295800</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:30</th>\n <td> 1.866889</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:40</th>\n <td>-0.486605</td>\n </tr>\n <tr>\n <th>2015-05-30 00:06:50</th>\n <td> 2.256074</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:00</th>\n <td>-1.655385</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:10</th>\n <td> 1.087934</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:20</th>\n <td> 0.107526</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:30</th>\n <td>-1.509951</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:40</th>\n <td>-0.798577</td>\n </tr>\n <tr>\n <th>2015-05-30 00:07:50</th>\n <td> 1.921219</td>\n </tr>\n <tr>\n <th>2015-05-30 00:08:00</th>\n <td>-1.495371</td>\n </tr>\n <tr>\n <th>2015-05-30 00:08:10</th>\n <td> 0.647703</td>\n </tr>\n </tbody>\n</table>\n</div>", | |
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