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jorisvandenbossche/gist:5305681

Created April 3, 2013 21:44
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gistfile1.txt
{
"metadata": {
"name": "test_hierarchical_index"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"Turin stationary data: Alphasenso CO sensor data investigation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"link [example link](#Test met de heading)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import datetime as dt\n",
"import pandas as pd\n",
"import os"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"Welcome to pylab, a matplotlib-based Python environment [backend: Qt4Agg].\n",
"For more information, type 'help(pylab)'.\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"arrays = [['SB1', 'SB1', 'SB2', 'SB2', 'SB3', 'SB3', 'SB4', 'SB4'],\n",
" ['co_alpha', 'temp', 'co_alpha', 'temp', 'co_alpha', 'temp', 'co_alpha', 'temp']]"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"tuples = zip(*arrays)\n",
"tuples"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 3,
"text": [
"[('SB1', 'co_alpha'),\n",
" ('SB1', 'temp'),\n",
" ('SB2', 'co_alpha'),\n",
" ('SB2', 'temp'),\n",
" ('SB3', 'co_alpha'),\n",
" ('SB3', 'temp'),\n",
" ('SB4', 'co_alpha'),\n",
" ('SB4', 'temp')]"
]
}
],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])\n",
"index"
],
"language": "python",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 4,
"text": [
"MultiIndex\n",
"[(SB1, co_alpha), (SB1, temp), (SB2, co_alpha), (SB2, temp), (SB3, co_alpha), (SB3, temp), (SB4, co_alpha), (SB4, temp)]"
]
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"s = pd.Series(randn(8), index=index)\n",
"s"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 5,
"text": [
"first second \n",
"SB1 co_alpha -0.672864\n",
" temp -1.785706\n",
"SB2 co_alpha -0.253444\n",
" temp 0.012696\n",
"SB3 co_alpha -1.071290\n",
" temp 0.665913\n",
"SB4 co_alpha -1.676434\n",
" temp 0.596448"
]
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pd.Series(randn(8), index=arrays)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 6,
"text": [
"SB1 co_alpha -1.331681\n",
" temp -0.786089\n",
"SB2 co_alpha 2.325138\n",
" temp 0.910780\n",
"SB3 co_alpha 0.105687\n",
" temp 0.037443\n",
"SB4 co_alpha -0.832341\n",
" temp -1.389372"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame(randn(4, 8), columns=arrays)\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th></th>\n",
" <th colspan=\"2\" halign=\"left\">SB1</th>\n",
" <th colspan=\"2\" halign=\"left\">SB2</th>\n",
" <th colspan=\"2\" halign=\"left\">SB3</th>\n",
" <th colspan=\"2\" halign=\"left\">SB4</th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.368326</td>\n",
" <td>-0.400795</td>\n",
" <td> 0.474947</td>\n",
" <td>-0.145894</td>\n",
" <td>-0.794057</td>\n",
" <td> 0.147168</td>\n",
" <td>-0.271703</td>\n",
" <td>-0.739156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 0.244511</td>\n",
" <td>-0.225491</td>\n",
" <td>-0.441524</td>\n",
" <td>-0.017268</td>\n",
" <td> 0.673915</td>\n",
" <td>-0.830436</td>\n",
" <td>-0.522951</td>\n",
" <td>-0.088112</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 0.441055</td>\n",
" <td> 0.866874</td>\n",
" <td>-0.281293</td>\n",
" <td>-0.892865</td>\n",
" <td>-0.016720</td>\n",
" <td> 0.789519</td>\n",
" <td> 0.316520</td>\n",
" <td>-0.947715</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1.137661</td>\n",
" <td>-0.103103</td>\n",
" <td> 0.258673</td>\n",
" <td>-0.801883</td>\n",
" <td> 1.613163</td>\n",
" <td> 1.246364</td>\n",
" <td> 0.118795</td>\n",
" <td>-0.960764</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 28,
"text": [
" SB1 SB2 SB3 SB4 \n",
" co_alpha temp co_alpha temp co_alpha temp co_alpha temp\n",
"0 -0.368326 -0.400795 0.474947 -0.145894 -0.794057 0.147168 -0.271703 -0.739156\n",
"1 0.244511 -0.225491 -0.441524 -0.017268 0.673915 -0.830436 -0.522951 -0.088112\n",
"2 0.441055 0.866874 -0.281293 -0.892865 -0.016720 0.789519 0.316520 -0.947715\n",
"3 1.137661 -0.103103 0.258673 -0.801883 1.613163 1.246364 0.118795 -0.960764"
]
}
],
"prompt_number": 28
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"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>co_alpha</th>\n",
" <th>temp</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.368326</td>\n",
" <td>-0.400795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 0.244511</td>\n",
" <td>-0.225491</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 0.441055</td>\n",
" <td> 0.866874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1.137661</td>\n",
" <td>-0.103103</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 29,
"text": [
" co_alpha temp\n",
"0 -0.368326 -0.400795\n",
"1 0.244511 -0.225491\n",
"2 0.441055 0.866874\n",
"3 1.137661 -0.103103"
]
}
],
"prompt_number": 29
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1']['co_alpha']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 30,
"text": [
"0 -0.368326\n",
"1 0.244511\n",
"2 0.441055\n",
"3 1.137661\n",
"Name: co_alpha"
]
}
],
"prompt_number": 30
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1', 'co_alpha']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 31,
"text": [
"0 -0.368326\n",
"1 0.244511\n",
"2 0.441055\n",
"3 1.137661\n",
"Name: (SB1, co_alpha)"
]
}
],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.xs('temp', axis=1, level=1)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"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>SB1</th>\n",
" <th>SB2</th>\n",
" <th>SB3</th>\n",
" <th>SB4</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.400795</td>\n",
" <td>-0.145894</td>\n",
" <td> 0.147168</td>\n",
" <td>-0.739156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>-0.225491</td>\n",
" <td>-0.017268</td>\n",
" <td>-0.830436</td>\n",
" <td>-0.088112</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 0.866874</td>\n",
" <td>-0.892865</td>\n",
" <td> 0.789519</td>\n",
" <td>-0.947715</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-0.103103</td>\n",
" <td>-0.801883</td>\n",
" <td> 1.246364</td>\n",
" <td>-0.960764</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 32,
"text": [
" SB1 SB2 SB3 SB4\n",
"0 -0.400795 -0.145894 0.147168 -0.739156\n",
"1 -0.225491 -0.017268 -0.830436 -0.088112\n",
"2 0.866874 -0.892865 0.789519 -0.947715\n",
"3 -0.103103 -0.801883 1.246364 -0.960764"
]
}
],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1', 'test'] = 0"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th></th>\n",
" <th colspan=\"2\" halign=\"left\">SB1</th>\n",
" <th colspan=\"2\" halign=\"left\">SB2</th>\n",
" <th colspan=\"2\" halign=\"left\">SB3</th>\n",
" <th colspan=\"2\" halign=\"left\">SB4</th>\n",
" <th>SB1</th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>test</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.368326</td>\n",
" <td>-0.400795</td>\n",
" <td> 0.474947</td>\n",
" <td>-0.145894</td>\n",
" <td>-0.794057</td>\n",
" <td> 0.147168</td>\n",
" <td>-0.271703</td>\n",
" <td>-0.739156</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 0.244511</td>\n",
" <td>-0.225491</td>\n",
" <td>-0.441524</td>\n",
" <td>-0.017268</td>\n",
" <td> 0.673915</td>\n",
" <td>-0.830436</td>\n",
" <td>-0.522951</td>\n",
" <td>-0.088112</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 0.441055</td>\n",
" <td> 0.866874</td>\n",
" <td>-0.281293</td>\n",
" <td>-0.892865</td>\n",
" <td>-0.016720</td>\n",
" <td> 0.789519</td>\n",
" <td> 0.316520</td>\n",
" <td>-0.947715</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1.137661</td>\n",
" <td>-0.103103</td>\n",
" <td> 0.258673</td>\n",
" <td>-0.801883</td>\n",
" <td> 1.613163</td>\n",
" <td> 1.246364</td>\n",
" <td> 0.118795</td>\n",
" <td>-0.960764</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 39,
"text": [
" SB1 SB2 SB3 SB4 SB1\n",
" co_alpha temp co_alpha temp co_alpha temp co_alpha temp test\n",
"0 -0.368326 -0.400795 0.474947 -0.145894 -0.794057 0.147168 -0.271703 -0.739156 0\n",
"1 0.244511 -0.225491 -0.441524 -0.017268 0.673915 -0.830436 -0.522951 -0.088112 0\n",
"2 0.441055 0.866874 -0.281293 -0.892865 -0.016720 0.789519 0.316520 -0.947715 0\n",
"3 1.137661 -0.103103 0.258673 -0.801883 1.613163 1.246364 0.118795 -0.960764 0"
]
}
],
"prompt_number": 39
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1']['test']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 17,
"text": [
"0 0\n",
"1 0\n",
"2 0\n",
"3 0\n",
"Name: test"
]
}
],
"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.columns"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 40,
"text": [
"MultiIndex\n",
"[(SB1, co_alpha), (SB1, temp), (SB2, co_alpha), (SB2, temp), (SB3, co_alpha), (SB3, temp), (SB4, co_alpha), (SB4, temp), (SB1, test)]"
]
}
],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['SB1']"
],
"language": "python",
"metadata": {},
"outputs": [
{
"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>co_alpha</th>\n",
" <th>temp</th>\n",
" <th>test</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.368326</td>\n",
" <td>-0.400795</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 0.244511</td>\n",
" <td>-0.225491</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 0.441055</td>\n",
" <td> 0.866874</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1.137661</td>\n",
" <td>-0.103103</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"output_type": "pyout",
"prompt_number": 41,
"text": [
" co_alpha temp test\n",
"0 -0.368326 -0.400795 0\n",
"1 0.244511 -0.225491 0\n",
"2 0.441055 0.866874 0\n",
"3 1.137661 -0.103103 0"
]
}
],
"prompt_number": 41
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame(randn(4, 8), columns=index)\n",
"df"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Test met de heading"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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