{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "df = pd.read_csv(\"tips.csv\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "\n", "Male 157\n", "Female 87\n", "Name: sex, dtype: int64" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df['sex'].value_counts()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "\n", "2 156\n", "3 38\n", "4 37\n", "5 5\n", "6 4\n", "1 4\n", "Name: size, dtype: int64" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df['size'].value_counts()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
\n", " | total_bill | \n", "tip | \n", "size | \n", "
---|---|---|---|
count | \n", "244.000000 | \n", "244.000000 | \n", "244.000000 | \n", "
mean | \n", "19.785943 | \n", "2.998279 | \n", "2.569672 | \n", "
std | \n", "8.902412 | \n", "1.383638 | \n", "0.951100 | \n", "
min | \n", "3.070000 | \n", "1.000000 | \n", "1.000000 | \n", "
25% | \n", "13.347500 | \n", "2.000000 | \n", "2.000000 | \n", "
50% | \n", "17.795000 | \n", "2.900000 | \n", "2.000000 | \n", "
75% | \n", "24.127500 | \n", "3.562500 | \n", "3.000000 | \n", "
max | \n", "50.810000 | \n", "10.000000 | \n", "6.000000 | \n", "