{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Pandas: When cell contents are lists, create a row for each element in the list\n", "\n", "https://stackoverflow.com/a/27266225/3744499" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "df = pd.DataFrame(\n", " {'trial_num': [1, 2, 3, 1, 2, 3],\n", " 'subject': [1, 1, 1, 2, 2, 2],\n", " 'samples': [list(np.random.randn(3).round(2)) for i in range(6)]\n", " }\n", ")" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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samplessubjecttrial_num
0[-1.92, 0.4, -0.54]11
1[0.42, -1.23, -0.23]12
2[0.43, -1.7, 1.25]13
3[-0.92, 1.41, 0.7]21
4[-1.88, 2.22, -0.68]22
5[-1.5, -1.36, -0.48]23
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subjecttrial_numlevel_20
0110-1.92
11110.40
2112-0.54
31200.42
4121-1.23
5122-0.23
61300.43
7131-1.70
81321.25
9210-0.92
102111.41
112120.70
12220-1.88
132212.22
14222-0.68
15230-1.50
16231-1.36
17232-0.48
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" ], "text/plain": [ " subject trial_num level_2 0\n", "0 1 1 0 -1.92\n", "1 1 1 1 0.40\n", "2 1 1 2 -0.54\n", "3 1 2 0 0.42\n", "4 1 2 1 -1.23\n", "5 1 2 2 -0.23\n", "6 1 3 0 0.43\n", "7 1 3 1 -1.70\n", "8 1 3 2 1.25\n", "9 2 1 0 -0.92\n", "10 2 1 1 1.41\n", "11 2 1 2 0.70\n", "12 2 2 0 -1.88\n", "13 2 2 1 2.22\n", "14 2 2 2 -0.68\n", "15 2 3 0 -1.50\n", "16 2 3 1 -1.36\n", "17 2 3 2 -0.48" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res = df.set_index(['subject', 'trial_num'])['samples'].apply(pd.Series).stack().reset_index()\n", "res" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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subjecttrial_numsample_numsample
0110-1.92
11110.40
2112-0.54
31200.42
4121-1.23
5122-0.23
61300.43
7131-1.70
81321.25
9210-0.92
102111.41
112120.70
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132212.22
14222-0.68
15230-1.50
16231-1.36
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" ], "text/plain": [ " subject trial_num sample_num sample\n", "0 1 1 0 -1.92\n", "1 1 1 1 0.40\n", "2 1 1 2 -0.54\n", "3 1 2 0 0.42\n", "4 1 2 1 -1.23\n", "5 1 2 2 -0.23\n", "6 1 3 0 0.43\n", "7 1 3 1 -1.70\n", "8 1 3 2 1.25\n", "9 2 1 0 -0.92\n", "10 2 1 1 1.41\n", "11 2 1 2 0.70\n", "12 2 2 0 -1.88\n", "13 2 2 1 2.22\n", "14 2 2 2 -0.68\n", "15 2 3 0 -1.50\n", "16 2 3 1 -1.36\n", "17 2 3 2 -0.48" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res.columns = ['subject','trial_num','sample_num','sample']\n", "res" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "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": "3.5.3" } }, "nbformat": 4, "nbformat_minor": 2 }