{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import random" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "names = [\"Albert\",\"John\",\"Richard\",\"Henry\",\"William\"]\n", "surnames = [\"Goodman\",\"Black\",\"White\",\"Green\",\"Joneson\"]\n", "salaries = [500*random.randint(10,30) for _ in range(10)]" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "def generate_random_person(names, surnames, salaries):\n", " return {\"name\":random.sample(names,1)[0],\n", " \"surname\":random.sample(surnames,1)[0],\n", " \"salary\":random.sample(salaries,1)[0]}\n", "def generate_people(k):\n", " return [generate_random_person(names, surnames, salaries) for _ in range(k)]" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'name': 'Richard', 'salary': 7500, 'surname': 'Joneson'}" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "generate_random_person(names, surnames, salaries)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "df = pd.DataFrame(generate_people(50),columns=[\"name\",\"surname\",\"salary\"])" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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namesurnamesalary
0HenryGoodman7500
1HenryBlack9500
2WilliamGoodman7000
3JohnBlack6000
4AlbertWhite9500
5WilliamGoodman7500
6RichardGreen12500
7AlbertGoodman7500
8AlbertJoneson12500
9RichardBlack6000
10WilliamGreen7500
11WilliamJoneson6000
12WilliamJoneson7500
13RichardGreen7000
14HenryGoodman9500
15RichardJoneson6000
16WilliamGreen8500
17JohnGreen7500
18HenryWhite9500
19JohnJoneson7000
20AlbertBlack7500
21RichardWhite7500
22RichardBlack8500
23HenryGoodman7500
24HenryBlack7000
25JohnGreen11500
26JohnBlack8500
27AlbertGreen11500
28JohnGoodman7500
29JohnWhite11500
30WilliamWhite7000
31JohnWhite9500
32AlbertGreen9500
33WilliamGreen6000
34WilliamBlack7000
35HenryWhite7000
36AlbertBlack7000
37JohnGoodman7500
38RichardWhite11500
39RichardGoodman7000
40HenryGreen7500
41RichardGoodman8500
42WilliamWhite11500
43JohnBlack12500
44JohnGreen7500
45RichardJoneson8500
46WilliamGoodman9500
47WilliamWhite6000
48AlbertBlack7000
49WilliamGreen12500
\n", "
" ], "text/plain": [ " name surname salary\n", "0 Henry Goodman 7500\n", "1 Henry Black 9500\n", "2 William Goodman 7000\n", "3 John Black 6000\n", "4 Albert White 9500\n", "5 William Goodman 7500\n", "6 Richard Green 12500\n", "7 Albert Goodman 7500\n", "8 Albert Joneson 12500\n", "9 Richard Black 6000\n", "10 William Green 7500\n", "11 William Joneson 6000\n", "12 William Joneson 7500\n", "13 Richard Green 7000\n", "14 Henry Goodman 9500\n", "15 Richard Joneson 6000\n", "16 William Green 8500\n", "17 John Green 7500\n", "18 Henry White 9500\n", "19 John Joneson 7000\n", "20 Albert Black 7500\n", "21 Richard White 7500\n", "22 Richard Black 8500\n", "23 Henry Goodman 7500\n", "24 Henry Black 7000\n", "25 John Green 11500\n", "26 John Black 8500\n", "27 Albert Green 11500\n", "28 John Goodman 7500\n", "29 John White 11500\n", "30 William White 7000\n", "31 John White 9500\n", "32 Albert Green 9500\n", "33 William Green 6000\n", "34 William Black 7000\n", "35 Henry White 7000\n", "36 Albert Black 7000\n", "37 John Goodman 7500\n", "38 Richard White 11500\n", "39 Richard Goodman 7000\n", "40 Henry Green 7500\n", "41 Richard Goodman 8500\n", "42 William White 11500\n", "43 John Black 12500\n", "44 John Green 7500\n", "45 Richard Joneson 8500\n", "46 William Goodman 9500\n", "47 William White 6000\n", "48 Albert Black 7000\n", "49 William Green 12500" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 2 }