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‎.ipynb_checkpoints/convert_categorical_to_numeric_naively-checkpoint.ipynb

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{
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"metadata": {
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"name": "",
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"signature": "sha256:d3d126284dab16155e99aca0e6e096469bfc319d5d5a33d5c0566e685cf6c24a"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Convert A String Categorical Variable To A Numeric Variable Naively\n",
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"\n",
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"This snippit was written by [Chris R. Albon](http://www.chrisralbon.com/) and is part of his collection of [well-documented Python snippits](https://github.com/chrisalbon/code_py). All code is written in Python 3 in iPython notebook and offered under the [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/).\n",
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"\n",
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"Originally from: Data Origami."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### import modules"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"import pandas as pd"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 2
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Create dataframe"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"raw_data = {'patient': [1, 1, 1, 2, 2], \n",
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" 'obs': [1, 2, 3, 1, 2], \n",
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" 'treatment': [0, 1, 0, 1, 0],\n",
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" 'score': ['strong', 'weak', 'normal', 'weak', 'strong']} \n",
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"df = pd.DataFrame(raw_data, columns = ['patient', 'obs', 'treatment', 'score'])\n",
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"df"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>patient</th>\n",
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" <th>obs</th>\n",
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" <th>treatment</th>\n",
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" <th>score</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> 1</td>\n",
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" <td> 1</td>\n",
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" <td> 0</td>\n",
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" <td> strong</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> 1</td>\n",
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" <td> 2</td>\n",
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" <td> 1</td>\n",
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" <td> weak</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> 1</td>\n",
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" <td> 3</td>\n",
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" <td> 0</td>\n",
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" <td> normal</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td> 2</td>\n",
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" <td> 1</td>\n",
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" <td> 1</td>\n",
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" <td> weak</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td> 2</td>\n",
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" <td> 2</td>\n",
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" <td> 0</td>\n",
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" <td> strong</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 3,
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"text": [
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" patient obs treatment score\n",
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"0 1 1 0 strong\n",
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"1 1 2 1 weak\n",
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"2 1 3 0 normal\n",
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"3 2 1 1 weak\n",
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"4 2 2 0 strong"
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]
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}
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],
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"prompt_number": 3
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Create a function that converts all values of df['score'] into numbers"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"def score_to_numeric(x):\n",
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" if x=='strong':\n",
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" return 3\n",
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" if x=='normal':\n",
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" return 2\n",
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" if x=='weak':\n",
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" return 1"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 5
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Apply the function to the score variable"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"df['score_num'] = df['score'].apply(score_to_numeric)\n",
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"df"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>patient</th>\n",
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" <th>obs</th>\n",
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" <th>treatment</th>\n",
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" <th>score</th>\n",
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" <th>score_num</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td> 1</td>\n",
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" <td> 1</td>\n",
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" <td> 0</td>\n",
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" <td> strong</td>\n",
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" <td> 3</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td> 1</td>\n",
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" <td> 2</td>\n",
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" <td> 1</td>\n",
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" <td> weak</td>\n",
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" <td> 1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td> 1</td>\n",
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" <td> 3</td>\n",
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" <td> 0</td>\n",
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" <td> normal</td>\n",
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" <td> 2</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td> 2</td>\n",
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" <td> 1</td>\n",
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" <td> 1</td>\n",
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" <td> weak</td>\n",
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" <td> 1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td> 2</td>\n",
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" <td> 2</td>\n",
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" <td> 0</td>\n",
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" <td> strong</td>\n",
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" <td> 3</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 7,
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"text": [
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" patient obs treatment score score_num\n",
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"0 1 1 0 strong 3\n",
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"1 1 2 1 weak 1\n",
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"2 1 3 0 normal 2\n",
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"3 2 1 1 weak 1\n",
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"4 2 2 0 strong 3"
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]
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}
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],
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"prompt_number": 7
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [],
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"language": "python",
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"metadata": {},
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"outputs": []
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}
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],
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"metadata": {}
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}
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]
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}

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