{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from io import StringIO \n",
"\n",
"data =\"\"\"Sample Animal Intelligence\n",
"1 Dog Dumb\n",
"2 Dog Dumb\n",
"3 Cat Smart\n",
"4 Cat Smart\n",
"5 Dog Smart\n",
"6 Cat Smart\"\"\"\n",
"dframe = pd.read_table(StringIO(data),sep='\\s+')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"
\n",
" \n",
" \n",
" | \n",
" Sample | \n",
" Animal | \n",
" Intelligence | \n",
"
\n",
" \n",
" \n",
" \n",
" 0 | \n",
" 1 | \n",
" Dog | \n",
" Dumb | \n",
"
\n",
" \n",
" 1 | \n",
" 2 | \n",
" Dog | \n",
" Dumb | \n",
"
\n",
" \n",
" 2 | \n",
" 3 | \n",
" Cat | \n",
" Smart | \n",
"
\n",
" \n",
" 3 | \n",
" 4 | \n",
" Cat | \n",
" Smart | \n",
"
\n",
" \n",
" 4 | \n",
" 5 | \n",
" Dog | \n",
" Smart | \n",
"
\n",
" \n",
" 5 | \n",
" 6 | \n",
" Cat | \n",
" Smart | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Sample Animal Intelligence\n",
"0 1 Dog Dumb\n",
"1 2 Dog Dumb\n",
"2 3 Cat Smart\n",
"3 4 Cat Smart\n",
"4 5 Dog Smart\n",
"5 6 Cat Smart"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dframe"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" Intelligence | \n",
" Dumb | \n",
" Smart | \n",
" All | \n",
"
\n",
" \n",
" Animal | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" \n",
" \n",
" Cat | \n",
" 0 | \n",
" 3 | \n",
" 3 | \n",
"
\n",
" \n",
" Dog | \n",
" 2 | \n",
" 1 | \n",
" 3 | \n",
"
\n",
" \n",
" All | \n",
" 2 | \n",
" 4 | \n",
" 6 | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
"Intelligence Dumb Smart All\n",
"Animal \n",
"Cat 0 3 3\n",
"Dog 2 1 3\n",
"All 2 4 6"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# クロス集計表が作れます。\n",
"pd.crosstab(dframe.Animal,dframe.Intelligence,margins=True)"
]
}
],
"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": "3.4.3"
}
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"nbformat": 4,
"nbformat_minor": 0
}