{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "# Project: Star Wars Survey Data Exploration\n", "\n", "In this project we will explore the responses of 1186 American [Star Wars](https://en.wikipedia.org/wiki/Star_Wars) fans. The data was collected by [FiveThirtyEight](https://fivethirtyeight.com/) team using the online tool [SurveyMonkey](https://www.surveymonkey.com/mp/audience/). The data set is downloadable from [FiveThirtyEight GitHub repository](https://github.com/fivethirtyeight/data/tree/master/star-wars-survey). It has several columns, including:\n", "\n", "* **`RespondentID`** : An anonymized ID for the respondent (person taking the survey)\n", "* **`Gender`** : The respondent's gender\n", "* **`Age`** : The respondent's age\n", "* **`Household Income`** : The respondent's income\n", "* **`Education`** : The respondent's education level\n", "* **`Location (Census Region)`** : The respondent's location\n", "* **`Have you seen any of the 6 films in the Star Wars franchise?`** : Has a Yes or No response\n", "* **`Do you consider yourself to be a fan of the Star Wars film franchise?`** : Has a Yes or No response\n", "\n", "At the end of this project we want to get answers for the following questions:\n", "\n", "* [**Wich Star Wars movie is the most popular among fans ?**](#question1)\n", "* [**Wich Star Wars movie is the most seen among fans ?**](#question2)\n", "* [**Wich Star Wars movie is the most popular among fans ? (by gender)**](#question3)\n", "* [**Wich Star Wars movie is the most seen among fans ? (by gender)**](#question4)\n", "* [**What is the location of Star Wars fans ?**](#question5)\n", "* [**What is the education level for Star Wars fans ?**](#question6)\n", "* [**Which character shot first ?**](#question7)\n", "* [**How old are fans of science fiction movies ?**](#question8)\n", "* [**Which character do respondents like the most ?** ](#question9)\n", "* [**Which character is the most controversial ?**](#question10)\n", "\n", "[Conclusion](#question11)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Importing Libraries" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np \n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Importing the dataset" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 1187 entries, 0 to 1186\n", "Data columns (total 38 columns):\n", "RespondentID 1186 non-null float64\n", "Have you seen any of the 6 films in the Star Wars franchise? 1187 non-null object\n", "Do you consider yourself to be a fan of the Star Wars film franchise? 837 non-null object\n", "Which of the following Star Wars films have you seen? Please select all that apply. 674 non-null object\n", "Unnamed: 4 572 non-null object\n", "Unnamed: 5 551 non-null object\n", "Unnamed: 6 608 non-null object\n", "Unnamed: 7 759 non-null object\n", "Unnamed: 8 739 non-null object\n", "Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. 836 non-null object\n", "Unnamed: 10 837 non-null object\n", "Unnamed: 11 836 non-null object\n", "Unnamed: 12 837 non-null object\n", "Unnamed: 13 837 non-null object\n", "Unnamed: 14 837 non-null object\n", "Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her. 830 non-null object\n", "Unnamed: 16 832 non-null object\n", "Unnamed: 17 832 non-null object\n", "Unnamed: 18 824 non-null object\n", "Unnamed: 19 826 non-null object\n", "Unnamed: 20 815 non-null object\n", "Unnamed: 21 827 non-null object\n", "Unnamed: 22 821 non-null object\n", "Unnamed: 23 813 non-null object\n", "Unnamed: 24 828 non-null object\n", "Unnamed: 25 831 non-null object\n", "Unnamed: 26 822 non-null object\n", "Unnamed: 27 815 non-null object\n", "Unnamed: 28 827 non-null object\n", "Which character shot first? 829 non-null object\n", "Are you familiar with the Expanded Universe? 829 non-null object\n", "Do you consider yourself to be a fan of the Expanded Universe?ξ 214 non-null object\n", "Do you consider yourself to be a fan of the Star Trek franchise? 1069 non-null object\n", "Gender 1047 non-null object\n", "Age 1047 non-null object\n", "Household Income 859 non-null object\n", "Education 1037 non-null object\n", "Location (Census Region) 1044 non-null object\n", "dtypes: float64(1), object(37)\n", "memory usage: 352.5+ KB\n" ] } ], "source": [ "# We need to specify the \"ISO-8859-1\" encoding because the data set has some characters that aren't in Python's default \"utf-8\" encoding.\n", "star_wars = pd.read_csv(\"star_wars.csv\", encoding=\"ISO-8859-1\")\n", "star_wars.info()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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RespondentIDHave you seen any of the 6 films in the Star Wars franchise?Do you consider yourself to be a fan of the Star Wars film franchise?Which of the following Star Wars films have you seen? Please select all that apply.Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film....Unnamed: 28Which character shot first?Are you familiar with the Expanded Universe?Do you consider yourself to be a fan of the Expanded Universe?ξDo you consider yourself to be a fan of the Star Trek franchise?GenderAgeHousehold IncomeEducationLocation (Census Region)
0NaNResponseResponseStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the JediStar Wars: Episode I The Phantom Menace...YodaResponseResponseResponseResponseResponseResponseResponseResponseResponse
13.292880e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi3...Very favorablyI don't understand this questionYesNoNoMale18-29NaNHigh school degreeSouth Atlantic
23.292880e+09NoNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNYesMale18-29$0 - $24,999Bachelor degreeWest South Central
33.292765e+09YesNoStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithNaNNaNNaN1...Unfamiliar (N/A)I don't understand this questionNoNaNNoMale18-29$0 - $24,999High school degreeWest North Central
43.292763e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi5...Very favorablyI don't understand this questionNoNaNYesMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
53.292731e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi5...Somewhat favorablyGreedoYesNoNoMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
63.292719e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi1...Very favorablyHanYesNoYesMale18-29$25,000 - $49,999Bachelor degreeMiddle Atlantic
73.292685e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi6...Very favorablyHanYesNoNoMale18-29NaNHigh school degreeEast North Central
83.292664e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi4...Very favorablyHanNoNaNYesMale18-29NaNHigh school degreeSouth Atlantic
93.292654e+09YesYesStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the Jedi5...Somewhat favorablyHanNoNaNNoMale18-29$0 - $24,999Some college or Associate degreeSouth Atlantic
\n", "

10 rows × 38 columns

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" ], "text/plain": [ " RespondentID Have you seen any of the 6 films in the Star Wars franchise? \\\n", "0 NaN Response \n", "1 3.292880e+09 Yes \n", "2 3.292880e+09 No \n", "3 3.292765e+09 Yes \n", "4 3.292763e+09 Yes \n", "5 3.292731e+09 Yes \n", "6 3.292719e+09 Yes \n", "7 3.292685e+09 Yes \n", "8 3.292664e+09 Yes \n", "9 3.292654e+09 Yes \n", "\n", " Do you consider yourself to be a fan of the Star Wars film franchise? \\\n", "0 Response \n", "1 Yes \n", "2 NaN \n", "3 No \n", "4 Yes \n", "5 Yes \n", "6 Yes \n", "7 Yes \n", "8 Yes \n", "9 Yes \n", "\n", " Which of the following Star Wars films have you seen? Please select all that apply. \\\n", "0 Star Wars: Episode I The Phantom Menace \n", "1 Star Wars: Episode I The Phantom Menace \n", "2 NaN \n", "3 Star Wars: Episode I The Phantom Menace \n", "4 Star Wars: Episode I The Phantom Menace \n", "5 Star Wars: Episode I The Phantom Menace \n", "6 Star Wars: Episode I The Phantom Menace \n", "7 Star Wars: Episode I The Phantom Menace \n", "8 Star Wars: Episode I The Phantom Menace \n", "9 Star Wars: Episode I The Phantom Menace \n", "\n", " Unnamed: 4 \\\n", "0 Star Wars: Episode II Attack of the Clones \n", "1 Star Wars: Episode II Attack of the Clones \n", "2 NaN \n", "3 Star Wars: Episode II Attack of the Clones \n", "4 Star Wars: Episode II Attack of the Clones \n", "5 Star Wars: Episode II Attack of the Clones \n", "6 Star Wars: Episode II Attack of the Clones \n", "7 Star Wars: Episode II Attack of the Clones \n", "8 Star Wars: Episode II Attack of the Clones \n", "9 Star Wars: Episode II Attack of the Clones \n", "\n", " Unnamed: 5 \\\n", "0 Star Wars: Episode III Revenge of the Sith \n", "1 Star Wars: Episode III Revenge of the Sith \n", "2 NaN \n", "3 Star Wars: Episode III Revenge of the Sith \n", "4 Star Wars: Episode III Revenge of the Sith \n", "5 Star Wars: Episode III Revenge of the Sith \n", "6 Star Wars: Episode III Revenge of the Sith \n", "7 Star Wars: Episode III Revenge of the Sith \n", "8 Star Wars: Episode III Revenge of the Sith \n", "9 Star Wars: Episode III Revenge of the Sith \n", "\n", " Unnamed: 6 \\\n", "0 Star Wars: Episode IV A New Hope \n", "1 Star Wars: Episode IV A New Hope \n", "2 NaN \n", "3 NaN \n", "4 Star Wars: Episode IV A New Hope \n", "5 Star Wars: Episode IV A New Hope \n", "6 Star Wars: Episode IV A New Hope \n", "7 Star Wars: Episode IV A New Hope \n", "8 Star Wars: Episode IV A New Hope \n", "9 Star Wars: Episode IV A New Hope \n", "\n", " Unnamed: 7 \\\n", "0 Star Wars: Episode V The Empire Strikes Back \n", "1 Star Wars: Episode V The Empire Strikes Back \n", "2 NaN \n", "3 NaN \n", "4 Star Wars: Episode V The Empire Strikes Back \n", "5 Star Wars: Episode V The Empire Strikes Back \n", "6 Star Wars: Episode V The Empire Strikes Back \n", "7 Star Wars: Episode V The Empire Strikes Back \n", "8 Star Wars: Episode V The Empire Strikes Back \n", "9 Star Wars: Episode V The Empire Strikes Back \n", "\n", " Unnamed: 8 \\\n", "0 Star Wars: Episode VI Return of the Jedi \n", "1 Star Wars: Episode VI Return of the Jedi \n", "2 NaN \n", "3 NaN \n", "4 Star Wars: Episode VI Return of the Jedi \n", "5 Star Wars: Episode VI Return of the Jedi \n", "6 Star Wars: Episode VI Return of the Jedi \n", "7 Star Wars: Episode VI Return of the Jedi \n", "8 Star Wars: Episode VI Return of the Jedi \n", "9 Star Wars: Episode VI Return of the Jedi \n", "\n", " Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. \\\n", "0 Star Wars: Episode I The Phantom Menace \n", "1 3 \n", "2 NaN \n", "3 1 \n", "4 5 \n", "5 5 \n", "6 1 \n", "7 6 \n", "8 4 \n", "9 5 \n", "\n", " ... Unnamed: 28 Which character shot first? \\\n", "0 ... Yoda Response \n", "1 ... Very favorably I don't understand this question \n", "2 ... NaN NaN \n", "3 ... Unfamiliar (N/A) I don't understand this question \n", "4 ... Very favorably I don't understand this question \n", "5 ... Somewhat favorably Greedo \n", "6 ... Very favorably Han \n", "7 ... Very favorably Han \n", "8 ... Very favorably Han \n", "9 ... Somewhat favorably Han \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "0 Response \n", "1 Yes \n", "2 NaN \n", "3 No \n", "4 No \n", "5 Yes \n", "6 Yes \n", "7 Yes \n", "8 No \n", "9 No \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe?ξ \\\n", "0 Response \n", "1 No \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "5 No \n", "6 No \n", "7 No \n", "8 NaN \n", "9 NaN \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? Gender \\\n", "0 Response Response \n", "1 No Male \n", "2 Yes Male \n", "3 No Male \n", "4 Yes Male \n", "5 No Male \n", "6 Yes Male \n", "7 No Male \n", "8 Yes Male \n", "9 No Male \n", "\n", " Age Household Income Education \\\n", "0 Response Response Response \n", "1 18-29 NaN High school degree \n", "2 18-29 $0 - $24,999 Bachelor degree \n", "3 18-29 $0 - $24,999 High school degree \n", "4 18-29 $100,000 - $149,999 Some college or Associate degree \n", "5 18-29 $100,000 - $149,999 Some college or Associate degree \n", "6 18-29 $25,000 - $49,999 Bachelor degree \n", "7 18-29 NaN High school degree \n", "8 18-29 NaN High school degree \n", "9 18-29 $0 - $24,999 Some college or Associate degree \n", "\n", " Location (Census Region) \n", "0 Response \n", "1 South Atlantic \n", "2 West South Central \n", "3 West North Central \n", "4 West North Central \n", "5 West North Central \n", "6 Middle Atlantic \n", "7 East North Central \n", "8 South Atlantic \n", "9 South Atlantic \n", "\n", "[10 rows x 38 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "star_wars.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data Cleaning" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['RespondentID',\n", " 'Have you seen any of the 6 films in the Star Wars franchise?',\n", " 'Do you consider yourself to be a fan of the Star Wars film franchise?',\n", " 'Which of the following Star Wars films have you seen? Please select all that apply.',\n", " 'Unnamed: 4', 'Unnamed: 5', 'Unnamed: 6', 'Unnamed: 7', 'Unnamed: 8',\n", " 'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.',\n", " 'Unnamed: 10', 'Unnamed: 11', 'Unnamed: 12', 'Unnamed: 13',\n", " 'Unnamed: 14',\n", " 'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.',\n", " 'Unnamed: 16', 'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19',\n", " 'Unnamed: 20', 'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23',\n", " 'Unnamed: 24', 'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27',\n", " 'Unnamed: 28', 'Which character shot first?',\n", " 'Are you familiar with the Expanded Universe?',\n", " 'Do you consider yourself to be a fan of the Expanded Universe?ξ',\n", " 'Do you consider yourself to be a fan of the Star Trek franchise?',\n", " 'Gender', 'Age', 'Household Income', 'Education',\n", " 'Location (Census Region)'],\n", " dtype='object')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting the names of columns\n", "star_wars.columns" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "45-60 291\n", "> 60 269\n", "30-44 268\n", "18-29 218\n", "NaN 140\n", "Response 1\n", "Name: Age, dtype: int64" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Age'\n", "star_wars['Age'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Female 549\n", "Male 497\n", "NaN 140\n", "Response 1\n", "Name: Gender, dtype: int64" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Gender'\n", "star_wars['Gender'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Some college or Associate degree 328\n", "Bachelor degree 321\n", "Graduate degree 275\n", "NaN 150\n", "High school degree 105\n", "Less than high school degree 7\n", "Response 1\n", "Name: Education, dtype: int64" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Education'\n", "star_wars['Education'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 328\n", "$50,000 - $99,999 298\n", "$25,000 - $49,999 186\n", "$100,000 - $149,999 141\n", "$0 - $24,999 138\n", "$150,000+ 95\n", "Response 1\n", "Name: Household Income, dtype: int64" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Household Income'\n", "star_wars['Household Income'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "East North Central 181\n", "Pacific 175\n", "South Atlantic 170\n", "NaN 143\n", "Middle Atlantic 122\n", "West South Central 110\n", "West North Central 93\n", "Mountain 79\n", "New England 75\n", "East South Central 38\n", "Response 1\n", "Name: Location (Census Region), dtype: int64" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Location (Census Region)'\n", "star_wars['Location (Census Region)'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is a common value between all the columns we have seen above which is `'Response'`, let's check this out deeply." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Investigating the row that contains 'Response'" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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RespondentIDHave you seen any of the 6 films in the Star Wars franchise?Do you consider yourself to be a fan of the Star Wars film franchise?Which of the following Star Wars films have you seen? Please select all that apply.Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film....Unnamed: 28Which character shot first?Are you familiar with the Expanded Universe?Do you consider yourself to be a fan of the Expanded Universe?ξDo you consider yourself to be a fan of the Star Trek franchise?GenderAgeHousehold IncomeEducationLocation (Census Region)
0NaNResponseResponseStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithStar Wars: Episode IV A New HopeStar Wars: Episode V The Empire Strikes BackStar Wars: Episode VI Return of the JediStar Wars: Episode I The Phantom Menace...YodaResponseResponseResponseResponseResponseResponseResponseResponseResponse
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1 rows × 38 columns

\n", "
" ], "text/plain": [ " RespondentID Have you seen any of the 6 films in the Star Wars franchise? \\\n", "0 NaN Response \n", "\n", " Do you consider yourself to be a fan of the Star Wars film franchise? \\\n", "0 Response \n", "\n", " Which of the following Star Wars films have you seen? Please select all that apply. \\\n", "0 Star Wars: Episode I The Phantom Menace \n", "\n", " Unnamed: 4 \\\n", "0 Star Wars: Episode II Attack of the Clones \n", "\n", " Unnamed: 5 \\\n", "0 Star Wars: Episode III Revenge of the Sith \n", "\n", " Unnamed: 6 \\\n", "0 Star Wars: Episode IV A New Hope \n", "\n", " Unnamed: 7 \\\n", "0 Star Wars: Episode V The Empire Strikes Back \n", "\n", " Unnamed: 8 \\\n", "0 Star Wars: Episode VI Return of the Jedi \n", "\n", " Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film. \\\n", "0 Star Wars: Episode I The Phantom Menace \n", "\n", " ... Unnamed: 28 Which character shot first? \\\n", "0 ... Yoda Response \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "0 Response \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe?ξ \\\n", "0 Response \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? Gender \\\n", "0 Response Response \n", "\n", " Age Household Income Education Location (Census Region) \n", "0 Response Response Response Response \n", "\n", "[1 rows x 38 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting the row that contains 'Response' \n", "star_wars.loc[star_wars['Age']=='Response',:]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The row that contains `'Response'` seems to be the header of the boxes to check in by the respondent in the survey, this row could have been created when the data was converted to columnar format. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see in the DataFrame above that the column `'Unnamed: 28'` contains the value `'Yoda'` which is the name of a character in Star Wars movies, let's check this out deeply." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Investigating columns from 'Unamed: 16' to 'Unamed: 28'." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28
0Luke SkywalkerPrincess Leia OrganaAnakin SkywalkerObi Wan KenobiEmperor PalpatineDarth VaderLando CalrissianBoba FettC-3P0R2 D2Jar Jar BinksPadme AmidalaYoda
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" ], "text/plain": [ " Unnamed: 16 Unnamed: 17 Unnamed: 18 Unnamed: 19 \\\n", "0 Luke Skywalker Princess Leia Organa Anakin Skywalker Obi Wan Kenobi \n", "\n", " Unnamed: 20 Unnamed: 21 Unnamed: 22 Unnamed: 23 Unnamed: 24 \\\n", "0 Emperor Palpatine Darth Vader Lando Calrissian Boba Fett C-3P0 \n", "\n", " Unnamed: 25 Unnamed: 26 Unnamed: 27 Unnamed: 28 \n", "0 R2 D2 Jar Jar Binks Padme Amidala Yoda " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting the row that contains 'Response' for columns 'Unamed: 16' to 'Unamed: 28'\n", "star_wars.loc[star_wars['Age']=='Response','Unnamed: 16' : 'Unnamed: 28']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The values above are the names of different characters in the Star Wars movies, it seems that they are related to the column `'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'` let's investigate that column." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Very favorably 610\n", "NaN 357\n", "Somewhat favorably 151\n", "Neither favorably nor unfavorably (neutral) 44\n", "Unfamiliar (N/A) 15\n", "Somewhat unfavorably 8\n", "Han Solo 1\n", "Very unfavorably 1\n", "Name: Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her., dtype: int64" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'\n", "star_wars['Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The column `'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'` contains also a name of Star Wars character wich is `'Han Solo'`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In summary, columns from **'Unamed: 16'** to **'Unamed: 28'** contain data on the respondents' point of view towards Star Wars characters. Each of the following columns can contain the value `Very favorably`, `Somewhat favorably`, `Unfamiliar (N/A)`, `Somewhat unfavorably`, `Very unfavorably`, or `NaN`:\n", "\n", "* **'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'** - How much the respondent liked the character 'Han Solo' \n", "* **'Unnamed: 16'** - How much the respondent liked the character **'Luke Skywalker'** \n", "* **'Unnamed: 17'** - How much the respondent liked the character **'Princess Leia Organa'** \n", "* **'Unnamed: 18'** - How much the respondent liked the character **'Anakin Skywalker'** \n", "* **'Unnamed: 19'** - How much the respondent liked the character **'Obi Wan Kenobi'** \n", "* **'Unnamed: 20'** - How much the respondent liked the character **'Emperor Palpatine'** \n", "* **'Unnamed: 21'** - How much the respondent liked the character **'Darth Vader'** \n", "* **'Unnamed: 22'** - How much the respondent liked the character **'Lando Calrissian'** \n", "* **'Unnamed: 23'** - How much the respondent liked the character **'Boba Fett'** \n", "* **'Unnamed: 24'** - How much the respondent liked the character **'C-3P0'** \n", "* **'Unnamed: 25'** - How much the respondent liked the character **'R2 D2'** \n", "* **'Unnamed: 26'** - How much the respondent liked the character **'Jar Jar Binks'** \n", "* **'Unnamed: 27'** - How much the respondent liked the character **'Padme Amidala'** \n", "* **'Unnamed: 28'** - How much the respondent liked the character **'Padme Yoda'** " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here we will save the names of the characters in a list for future use." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Han Solo',\n", " 'Luke Skywalker',\n", " 'Princess Leia Organa',\n", " 'Anakin Skywalker',\n", " 'Obi Wan Kenobi',\n", " 'Emperor Palpatine',\n", " 'Darth Vader',\n", " 'Lando Calrissian',\n", " 'Boba Fett',\n", " 'C-3P0',\n", " 'R2 D2',\n", " 'Jar Jar Binks',\n", " 'Padme Amidala',\n", " 'Yoda']" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "characters = star_wars.iloc[0, 15:29].values.tolist()\n", "characters" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Investigating columns from 'Unamed: 4' to 'Unamed: 8'." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 615\n", "Star Wars: Episode II Attack of the Clones 572\n", "Name: Unnamed: 4, dtype: int64" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Unnamed: 4'\n", "star_wars['Unnamed: 4'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Star Wars: Episode VI Return of the Jedi 739\n", "NaN 448\n", "Name: Unnamed: 8, dtype: int64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Unnamed: 8'\n", "star_wars['Unnamed: 8'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The columns **'Unamed: 4'** to **'Unamed: 8'** represent a single checkbox question that are related to the question, **'Which of the following Star Wars films have you seen? Please select all that apply.'**" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Star Wars: Episode I The Phantom Menace 674\n", "NaN 513\n", "Name: Which of the following Star Wars films have you seen? Please select all that apply., dtype: int64" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Which of the following Star Wars films have you seen? Please select all that apply.'\n", "star_wars['Which of the following Star Wars films have you seen? Please select all that apply.'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In summary, the following columns are related to the question \"`Which of the following Star Wars films have you seen?`\" :\n", "\n", "* **Which of the following Star Wars films have you seen? Please select all that apply.** - Whether or not the respondent saw Star Wars: Episode I The Phantom Menace.\n", "* **Unnamed: 4** - Whether or not the respondent saw Star Wars: Episode II Attack of the Clones.\n", "* **Unnamed: 5** - Whether or not the respondent saw Star Wars: Episode III Revenge of the Sith.\n", "* **Unnamed: 6** - Whether or not the respondent saw Star Wars: Episode IV A New Hope.\n", "* **Unnamed: 7** - Whether or not the respondent saw Star Wars: Episode V The Empire Strikes Back.\n", "* **Unnamed: 8** - Whether or not the respondent saw Star Wars: Episode VI Return of the Jedi." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Investigating columns from 'Unamed: 10' to 'Unamed: 14'." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 350\n", "5 300\n", "4 183\n", "2 116\n", "3 103\n", "6 102\n", "1 32\n", "Star Wars: Episode II Attack of the Clones 1\n", "Name: Unnamed: 10, dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Unnamed: 10'\n", "star_wars['Unnamed: 10'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 350\n", "2 232\n", "3 220\n", "1 146\n", "6 145\n", "4 57\n", "5 36\n", "Star Wars: Episode VI Return of the Jedi 1\n", "Name: Unnamed: 14, dtype: int64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Unnamed: 14'\n", "star_wars['Unnamed: 14'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 351\n", "4 237\n", "6 168\n", "3 130\n", "1 129\n", "5 100\n", "2 71\n", "Star Wars: Episode I The Phantom Menace 1\n", "Name: Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film., dtype: int64" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.'\n", "star_wars['Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Columns from **Unamed: 10** to **Unamed: 14** ask the respondent to rank the Star Wars movies in order of least favorite to most favorite. 1 means the film was the most favorite, and 6 means it was the least favorite. Each of the following columns can contain the value 1, 2, 3, 4, 5, 6, or NaN:\n", "\n", "* **Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.** - How much the respondent liked Star Wars: Episode I The Phantom Menace\n", "* **Unnamed: 10** - How much the respondent liked Star Wars: Episode II Attack of the Clones\n", "* **Unnamed: 11** - How much the respondent liked Star Wars: Episode III Revenge of the Sith\n", "* **Unnamed: 12** - How much the respondent liked Star Wars: Episode IV A New Hope\n", "* **Unnamed: 13** - How much the respondent liked Star Wars: Episode V The Empire Strikes Back\n", "* **Unnamed: 14** - How much the respondent liked Star Wars: Episode VI Return of the Jedi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Data quality notes." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "* **'RespondentID'** contains NaN values that we need to remove.\n", "* Columns like **'Have you seen any of the 6 films in the Star Wars franchise?'** and **'Do you consider yourself to be a fan of the Star Wars film franchise?'** are currently string types, because the main values they contain are 'Yes' and 'No'. We can make the data a bit easier to analyze by converting them to a Boolean having only the values True, False, and NaN.\n", "* The names of columns **'Which of the following Star Wars films have you seen? Please select all that apply.'** to **'Unnamed: 8'** need to be more intuitive, the same case with columns from **'Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.'** to **'Unamed: 14'** and columns from **'Please state whether you view the following characters favorably, unfavorably, or are unfamiliar with him/her.'** to **'Unnamed: 28'**.\n", "* Columns **'Which of the following Star Wars films have you seen? Please select all that apply.'** to **'Unnamed: 8'** are object type. We'll need to convert each of these columns to a Boolean 'True' and 'False' values.\n", "* We need to remove the strange Characters from **'Do you consider yourself to be a fan of the Expanded Universe?ξ'**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Remove any rows where RespondentID is NaN." ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "scrolled": false }, "outputs": [], "source": [ "# Remove any rows where RespondentID is NaN\n", "star_wars = star_wars[star_wars['RespondentID'].notnull()]" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The number of rows is 1186\n" ] } ], "source": [ "print('The number of rows is',star_wars.shape[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Renaming columns." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['RespondentID',\n", " 'Have you seen any of the 6 films in the Star Wars franchise?',\n", " 'Do you consider yourself to be a fan of the Star Wars film franchise?',\n", " 'I saw Star Wars: Episode I The Phantom Menace',\n", " 'I saw Star Wars: Episode II Attack of the Clones',\n", " 'I saw Star Wars: Episode III Revenge of the Sith',\n", " 'I saw Star Wars: Episode IV A New Hope',\n", " 'I saw Star Wars: Episode V The Empire Strikes Back',\n", " 'I saw Star Wars: Episode VI Return of the Jedi',\n", " 'Star Wars: Episode I The Phantom Menace rank',\n", " 'Star Wars: Episode II Attack of the Clones rank',\n", " 'Star Wars: Episode III Revenge of the Sith rank',\n", " 'Star Wars: Episode IV A New Hope rank',\n", " 'Star Wars: Episode V The Empire Strikes Back rank',\n", " 'Star Wars: Episode VI Return of the Jedi rank', 'Han Solo',\n", " 'Luke Skywalker', 'Princess Leia Organa', 'Anakin Skywalker',\n", " 'Obi Wan Kenobi', 'Emperor Palpatine', 'Darth Vader',\n", " 'Lando Calrissian', 'Boba Fett', 'C-3P0', 'R2 D2', 'Jar Jar Binks',\n", " 'Padme Amidala', 'Yoda', 'Which character shot first?',\n", " 'Are you familiar with the Expanded Universe?',\n", " 'Do you consider yourself to be a fan of the Expanded Universe?',\n", " 'Do you consider yourself to be a fan of the Star Trek franchise?',\n", " 'Gender', 'Age', 'Household Income', 'Education',\n", " 'Location (Census Region)'],\n", " dtype='object')" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Renaming columns related to the question 'Which of the following Star Wars films have you seen?'\n", "i_saw_it = {\"Which of the following Star Wars films have you seen? Please select all that apply.\": \"I saw Star Wars: Episode I The Phantom Menace\",\n", " \"Unnamed: 4\": \"I saw Star Wars: Episode II Attack of the Clones\",\n", " \"Unnamed: 5\": \"I saw Star Wars: Episode III Revenge of the Sith\",\n", " \"Unnamed: 6\": \"I saw Star Wars: Episode IV A New Hope\",\n", " \"Unnamed: 7\": \"I saw Star Wars: Episode V The Empire Strikes Back\",\n", " \"Unnamed: 8\": \"I saw Star Wars: Episode VI Return of the Jedi\"}\n", "star_wars.rename(columns=i_saw_it,inplace=True)\n", "\n", "# Renaming columns related to the question 'Please rank the Star Wars films in order of preference\n", "# with 1 being your favorite film in the franchise and 6 being your least favorite film.' \n", "ranking = {\"Please rank the Star Wars films in order of preference with 1 being your favorite film in the franchise and 6 being your least favorite film.\": \"Star Wars: Episode I The Phantom Menace rank\",\n", " \"Unnamed: 10\": \"Star Wars: Episode II Attack of the Clones rank\",\n", " \"Unnamed: 11\": \"Star Wars: Episode III Revenge of the Sith rank\",\n", " \"Unnamed: 12\": \"Star Wars: Episode IV A New Hope rank\",\n", " \"Unnamed: 13\": \"Star Wars: Episode V The Empire Strikes Back rank\",\n", " \"Unnamed: 14\": \"Star Wars: Episode VI Return of the Jedi rank\"}\n", "star_wars.rename(columns=ranking,inplace=True)\n", "\n", "# Renaming columns related to the question 'Please state whether you view the following characters \n", "#favorably, unfavorably, or are unfamiliar with him/her.\n", "star_wars_characters = dict(zip(star_wars.columns[15:29],characters))\n", "star_wars.rename(columns=star_wars_characters,inplace=True)\n", "\n", "# remove strange characters from 'Do you consider yourself to be a fan of the Expanded Universe?ξ\n", "star_wars.columns = star_wars.columns.str.replace('ξ','')\n", "\n", "star_wars.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Converting columns from position 3 to 8 into Boolean type. \n", "We will convert the columns from position 3 to 8 so that they contain only the values True and False, if the value in a cell is the name of the movie, that means the respondent saw the movie. If the value is NaN, the respondent either didn't answer or didn't see the movie. We'll assume that they didn't see the movie." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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I saw Star Wars: Episode I The Phantom MenaceI saw Star Wars: Episode II Attack of the ClonesI saw Star Wars: Episode III Revenge of the SithI saw Star Wars: Episode IV A New HopeI saw Star Wars: Episode V The Empire Strikes BackI saw Star Wars: Episode VI Return of the Jedi
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" ], "text/plain": [ " I saw Star Wars: Episode I The Phantom Menace \\\n", "1 True \n", "2 False \n", "3 True \n", "4 True \n", "5 True \n", "\n", " I saw Star Wars: Episode II Attack of the Clones \\\n", "1 True \n", "2 False \n", "3 True \n", "4 True \n", "5 True \n", "\n", " I saw Star Wars: Episode III Revenge of the Sith \\\n", "1 True \n", "2 False \n", "3 True \n", "4 True \n", "5 True \n", "\n", " I saw Star Wars: Episode IV A New Hope \\\n", "1 True \n", "2 False \n", "3 False \n", "4 True \n", "5 True \n", "\n", " I saw Star Wars: Episode V The Empire Strikes Back \\\n", "1 True \n", "2 False \n", "3 False \n", "4 True \n", "5 True \n", "\n", " I saw Star Wars: Episode VI Return of the Jedi \n", "1 True \n", "2 False \n", "3 False \n", "4 True \n", "5 True " ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# define a function that update the value to True if the value is the name of the movie, False if the value is None.\n", "def update_val(val):\n", " if val in [\"Star Wars: Episode I The Phantom Menace\",\n", " \"Star Wars: Episode II Attack of the Clones\",\n", " \"Star Wars: Episode III Revenge of the Sith\",\n", " \"Star Wars: Episode IV A New Hope\",\n", " \"Star Wars: Episode V The Empire Strikes Back\",\n", " \"Star Wars: Episode VI Return of the Jedi\"]:\n", " return True\n", " else:\n", " return False\n", "\n", "# apply the update_val element-wise on columns from position 3 to 8. \n", "star_wars[star_wars.columns[3:9]] = star_wars[star_wars.columns[3:9]].applymap(update_val)\n", "star_wars[star_wars.columns[3:9]].head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Changing 'Yes' and 'No' values into 'True' and 'False'\n", "We will convert each column of the list bellow to a Boolean having only the values True, False, and NaN. \n", "* ***Have you seen any of the 6 films in the Star Wars franchise?***\n", "* ***Do you consider yourself to be a fan of the Star Wars film franchise?***\n", "* ***Are you familiar with the Expanded Universe?***\t\n", "* ***Do you consider yourself to be a fan of the Expanded Universe?***\t\n", "* ***Do you consider yourself to be a fan of the Star Trek franchise?***" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Have you seen any of the 6 films in the Star Wars franchise?Do you consider yourself to be a fan of the Star Wars film franchise?Are you familiar with the Expanded Universe?Do you consider yourself to be a fan of the Expanded Universe?Do you consider yourself to be a fan of the Star Trek franchise?
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" ], "text/plain": [ " Have you seen any of the 6 films in the Star Wars franchise? \\\n", "1 True \n", "2 False \n", "3 True \n", "4 True \n", "5 True \n", "\n", " Do you consider yourself to be a fan of the Star Wars film franchise? \\\n", "1 True \n", "2 None \n", "3 False \n", "4 True \n", "5 True \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "1 True \n", "2 None \n", "3 False \n", "4 False \n", "5 True \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe? \\\n", "1 False \n", "2 None \n", "3 None \n", "4 None \n", "5 False \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? \n", "1 False \n", "2 True \n", "3 False \n", "4 True \n", "5 False " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# define a function that change 'Yes' to 'True' and 'No' to 'False'.\n", "def yes_no(val):\n", " if val == \"Yes\":\n", " return True\n", " elif val == \"No\":\n", " return False\n", "\n", "# apply the function yes_no element-wise on columns with position 1,2,30,31 and 32. \n", "star_wars[star_wars.columns[[1,2,30,31,32]]] = star_wars[star_wars.columns[[1,2,30,31,32]]].applymap(yes_no)\n", "star_wars[star_wars.columns[[1,2,30,31,32]]].head()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## Data Analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Recall that the respondent was asked to rank the Star Wars movies in order of least favorite to most favorite. 1 means the film was the most favorite, and 6 means it was the least favorite. Now that we've cleaned up the ranking columns, we can find the highest-ranked movie more quickly. To do this, we will take the mean of each of the ranking columns using the pandas. DataFrame.mean() method on dataframes wich means that the movie with the lowest ranking is the best!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### The most popular Star Wars movie" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# find the mean of each of the ranking columns\n", "ranking = star_wars[star_wars.columns[9:15]].astype(float).mean(axis=0)\n", "# visualization \n", "fig , ax = plt.subplots(figsize=[8,5])\n", "ax = star_wars[star_wars.columns[9:15]].astype(float).mean(axis=0).plot.barh(color='blue')\n", "# remove x ticks labels\n", "ax.set_xticks([])\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# set title\n", "ax.set_title('Star Wars movies ranked by repondents',size=15)\n", "# remove y ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# add padding between axes and labels set y label size\n", "ax.xaxis.set_tick_params(pad=5)\n", "ax.yaxis.set_tick_params(pad=10,labelsize=12)\n", "# annotation\n", "for p, q in zip(ax.patches, ranking.index.values.tolist()):\n", " ax.text(p.get_width()+.1,p.get_y()+p.get_height()/2-.1,'rank '+str(ranking.sort_values(ascending=True).index.values.tolist().index(q)+1),size=12)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In general, fans seem to prefer the original trilogy of the cinematic saga of Star Wars which consists of \"A New Hope (1977)\", \"The Empire Strikes Back (1980)\" and \"Return of the Jedi (1983)\". The trilogy was the first epic science fiction space adventure to be told on a large scale that is why it holds a special place in the hearts of Star Wars fans. `\"Star Wars: Episode V The Empire Strikes Back\"` is considered by the respondents to be the best film in the saga." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### The most seen Star Wars movie" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[8,5])\n", "ax = star_wars[star_wars.columns[3:9]].sum(axis=0).sort_values().plot.barh(color='blue')\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x ticks labels\n", "ax.set_xticklabels([])\n", "# set title\n", "ax.set_title('The most seen Star Wars Movie',size=15)\n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# add padding between axes and labels\n", "ax.xaxis.set_tick_params(pad=5)\n", "ax.yaxis.set_tick_params(pad=10,labelsize=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`\"Star Wars: Episode V The Empire Strikes Back\"` is the most seen Star Wars movie by the respondents. In general the results correlate positively with the ranking, the more the movie is popular, the more it is watched." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### The most popular Star Wars movie by gender" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# star wars movies names\n", "sw_movies_rank = star_wars.columns[9:15]\n", "# male's preferences\n", "male_preference = star_wars.loc[star_wars[\"Gender\"] == \"Male\",sw_movies_rank].astype(float).mean()\n", "# female's preferences\n", "female_preference = star_wars.loc[star_wars[\"Gender\"] == \"Female\",sw_movies_rank].astype(float).mean()\n", "\n", "# visualization :\n", "fig,ax = plt.subplots(figsize=[8,5])\n", "\n", "y_index = np.array([0,1.5,3,4.5,6,7.5])\n", "height = .5\n", "# plotting male_preference \n", "m = ax.barh(y_index ,male_preference,height)\n", "# plotting female_preference \n", "f= ax.barh(y_index+height ,female_preference,height,color='orange')\n", "# set y axis ticks and labels\n", "ax.set_yticks(y_index+.5)\n", "ax.set_yticklabels(labels=sw_movies_rank.values)\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# remove x ticks labels\n", "ax.set_xticklabels([])\n", "# set title\n", "ax.set_title('Star Wars movies ranked by Gender',size=15)\n", "# legend\n", "ax.legend((m, f), ('Male', 'Female'))\n", "# annotation_male\n", "for p, q in zip(m.patches, male_preference.index.values.tolist()):\n", " ax.text(p.get_width()+.1,p.get_y()+p.get_height()/2-.13,'rank '+str(male_preference.sort_values(ascending=True).index.values.tolist().index(q)+1),size=10)\n", "# annotation_female\n", "for p, q in zip(f.patches, female_preference.index.values.tolist()):\n", " ax.text(p.get_width()+.1,p.get_y()+p.get_height()/2-.13,'rank '+str(female_preference.sort_values(ascending=True).index.values.tolist().index(q)+1),size=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`\"Episode V: The Empire Strikes Back\"` is the most popular Star Wars film among female and male fans. Men rated the three original movies at the top of their favorite Star Wars films while only two of the original movies were highly rated by women, they considered `\" Episode I: The Phantom Menace 1999\"` is more popular than `\"Episode IV: A New Hope 1977\"`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### The most seen Star Wars movie by gender" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "seen = star_wars.columns[3:9]\n", "seen_movie_by_male = star_wars.loc[star_wars[\"Gender\"] == \"Male\",seen].astype(float).sum()\n", "seen_movie_by_female = star_wars.loc[star_wars[\"Gender\"] == \"Female\",seen].astype(float).sum()\n", "\n", "fig,ax = plt.subplots(figsize=[8,5])\n", "\n", "y_index = np.array([0,1.5,3,4.5,6,7.5])\n", "height = .5\n", "\n", "m = ax.barh(y_index ,seen_movie_by_male,height)\n", "f= ax.barh(y_index+height ,seen_movie_by_female,height,color='orange')\n", "# set y axis ticks and labels\n", "ax.set_yticks(y_index+.5)\n", "ax.set_yticklabels(labels=seen.values)\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# remove x ticks labels\n", "ax.set_xticklabels([])\n", "# set title\n", "ax.set_title('The most seen Star Wars movie by Gender',size=15)\n", "# set legend\n", "ax.legend((m, f), ('Male', 'Female'),loc='center right',bbox_to_anchor=(1.1, 0.3))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Star Wars movies are more popular among men than women, `\"Episode V The Empire Striked Back\"` is the most watched Star Wars movie among both of men and women." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Location of Star wars fans respondents\n", "\n", "We will focus here on respondents who consider themselves to be a fan of Star Wars film franchise." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True 552\n", "NaN 350\n", "False 284\n", "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].value_counts(dropna=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will fill nan values with False values." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False 634\n", "True 552\n", "Name: Do you consider yourself to be a fan of the Star Wars film franchise?, dtype: int64" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?']=star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].fillna(False)\n", "star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Star Wars fans location')" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[8,5])\n", "ax= (star_wars.loc[star_wars['Do you consider yourself to be a fan of the Star Trek franchise?'] == True,'Location (Census Region)'].value_counts()*100/552).plot.barh(color='blue')\n", "\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# set x axis label\n", "ax.set_xlabel('%')\n", "# set title\n", "ax.set_title('Star Wars fans location',size=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Most of the Star Wars fans who responded to the survey are located in the South Atlantic states, the East North Central, the Pacific and the Middle Atlantic." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Education level for Star Wars fans" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Education level for Star Wars fans who responded to the survey')" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[8,5])\n", "\n", "ax= (star_wars.loc[star_wars['Do you consider yourself to be a fan of the Star Trek franchise?'] == True,'Education'].value_counts()*100/552).plot.barh(color='blue')\n", "\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# set x axis label\n", "ax.set_xlabel('%')\n", "# set title\n", "ax.set_title('Education level for Star Wars fans who responded to the survey',size=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "95% of the Star Wars fans who respond to the survey have more than a High school degree." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Which character shot first?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**`'Which character shot first?'`** ` {1} this question refers to a controversial change made to a scene in the science fiction action film Star Wars (1977), in which Han Solo (Harrison Ford) is confronted by the bounty hunter Greedo (Paul Blake) in the Mos Eisley cantina. In the original version of the scene, Han shoots Greedo dead. Later versions are edited so that Greedo attempts to fire at Han first. Director George Lucas altered the scene to give Solo more justification for acting in self-defense. Many fans and commentators oppose the change, feeling it weakens Solo's character. The controversy is referenced in the 2018 film Solo: A Star Wars Story.`\n", "\n", "\n", "`{1}: Wikipedia.`\n" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "NaN 358\n", "Han 325\n", "I don't understand this question 306\n", "Greedo 197\n", "Name: Which character shot first?, dtype: int64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# inspecting unique values in 'Which character shot first?'.\n", "star_wars['Which character shot first?'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "I don't understand this question 664\n", "Han 325\n", "Greedo 197\n", "Name: Which character shot first?, dtype: int64" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# filling the nan values with 'I don't understand this question'\n", "star_wars['Which character shot first?']=star_wars['Which character shot first?'].fillna(\"I don't understand this question\")\n", "star_wars['Which character shot first?'].value_counts(dropna=False)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[5,5])\n", "ax = star_wars.loc[star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?'] == True,'Which character shot first?']\\\n", ".value_counts(dropna=False).plot.pie(autopct='%1.1f%%',explode=[0.03,0,0], startangle=90)\n", "ax.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.\n", "ax.set_ylabel('')\n", "ax.set_title('Which character shot first?').set_position([.5, 1.05])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "About half of Star Wars fans are confident that 'Han Solo' shot first in the other hand 27% believe that 'Greedo' shot first. Despite considering themselves to be Star Wars fans, 24% of them did not understand the question which is a bit contradictory." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Science fiction movies fans by age\n", "Here we will be interested in the age of sci-fi movies passionates, we will consider any respondent who is both a fan of star wars and star trek as such." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "geek=(star_wars['Do you consider yourself to be a fan of the Star Trek franchise?'] == True) & (star_wars['Do you consider yourself to be a fan of the Star Wars film franchise?']==True)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[5,5])\n", "ax= (star_wars.loc[geek,'Age'].value_counts()*100/geek.astype(int).sum()).plot.pie(autopct='%1.1f%%',explode=[0,0,0,0], startangle=90)\n", "ax.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle.\n", "ax.set_ylabel('')\n", "ax.set_title('Science fiction movie fans by age categories').set_position([.5, 1.05])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "About 25% of science fiction movie fans are over the age of 60!. It seems that the old prefer science fiction films more than the young." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Which character do respondents like the most ?" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Han Solo Luke Skywalker Princess Leia Organa \\\n", "1 Very favorably Very favorably Very favorably \n", "2 NaN NaN NaN \n", "3 Somewhat favorably Somewhat favorably Somewhat favorably \n", "4 Very favorably Very favorably Very favorably \n", "5 Very favorably Somewhat favorably Somewhat favorably \n", "\n", " Anakin Skywalker Obi Wan Kenobi Emperor Palpatine \\\n", "1 Very favorably Very favorably Very favorably \n", "2 NaN NaN NaN \n", "3 Somewhat favorably Somewhat favorably Unfamiliar (N/A) \n", "4 Very favorably Very favorably Somewhat favorably \n", "5 Somewhat unfavorably Very favorably Very unfavorably \n", "\n", " Darth Vader Lando Calrissian \\\n", "1 Very favorably Unfamiliar (N/A) \n", "2 NaN NaN \n", "3 Unfamiliar (N/A) Unfamiliar (N/A) \n", "4 Very favorably Somewhat favorably \n", "5 Somewhat favorably Neither favorably nor unfavorably (neutral) \n", "\n", " Boba Fett C-3P0 R2 D2 \\\n", "1 Unfamiliar (N/A) Very favorably Very favorably \n", "2 NaN NaN NaN \n", "3 Unfamiliar (N/A) Unfamiliar (N/A) Unfamiliar (N/A) \n", "4 Somewhat unfavorably Very favorably Very favorably \n", "5 Very favorably Somewhat favorably Somewhat favorably \n", "\n", " Jar Jar Binks Padme Amidala Yoda \n", "1 Very favorably Very favorably Very favorably \n", "2 NaN NaN NaN \n", "3 Unfamiliar (N/A) Unfamiliar (N/A) Unfamiliar (N/A) \n", "4 Very favorably Very favorably Very favorably \n", "5 Very unfavorably Somewhat favorably Somewhat favorably " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "characters = star_wars[star_wars.columns[15:29]]\n", "characters.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will create a function that converts the respondent's point of view towards a Star Wars character to a score ranging from -2 to 2 we will then apply the sum of the scores for each character, the character with the highest score is the most appreciated by the respondents." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "# create a function that converts the respondent's point of view towards a star wars character to a score ranging from -2 to 2.\n", "def update_val(val):\n", " if val=='Very favorably':\n", " return 2\n", " elif val=='Somewhat favorably':\n", " return 1\n", " elif val in ['Neither favorably nor unfavorably (neutral)' , 'Unfamiliar (N/A)',np.nan]:\n", " return 0\n", " elif val == 'Very unfavorably':\n", " return -2\n", " elif val == 'Somewhat unfavorably':\n", " return -1\n", "# apply the update_val element-wise on columns with position 15 to 28. \n", "characters = characters.applymap(update_val)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Han Solo Luke Skywalker Princess Leia Organa Anakin Skywalker \\\n", "1 2 2 2 2 \n", "2 0 0 0 0 \n", "3 1 1 1 1 \n", "4 2 2 2 2 \n", "5 2 1 1 -1 \n", "\n", " Obi Wan Kenobi Emperor Palpatine Darth Vader Lando Calrissian \\\n", "1 2 2 2 0 \n", "2 0 0 0 0 \n", "3 1 0 0 0 \n", "4 2 1 2 1 \n", "5 2 -2 1 0 \n", "\n", " Boba Fett C-3P0 R2 D2 Jar Jar Binks Padme Amidala Yoda \n", "1 0 2 2 2 2 2 \n", "2 0 0 0 0 0 0 \n", "3 0 0 0 0 0 0 \n", "4 -1 2 2 2 2 2 \n", "5 2 1 1 -2 1 1 " ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "characters.head()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Characters popularity')" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig,ax = plt.subplots(figsize=[8,5])\n", "\n", "ax= characters.sum(axis=0).plot.barh()\n", "\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# set title\n", "ax.set_title('Characters popularity',size=12)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "'Yoda' and 'Han Solo' are the respondents' favorite characters, in contrast 'Jar Jar Binks' is the least popular among the characters." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### Which character is the most controversial ?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To find the most controversial character we need to split between the likes and the dislikes of each character to do that we are going to create a function that convert scores into 'like', 'dislike' and 'neutral'." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "# create a function that converts scores into likes, dislikes and neutral.\n", "def like_dislike(val):\n", " if val > 0 :\n", " return 'like'\n", " elif val < 0 :\n", " return 'dislike'\n", " elif val == 0:\n", " return 'neutral'\n", "# apply the like_dislike element-wise on columns with position 15 to 29. \n", "characters = characters.applymap(like_dislike)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Han Solo Luke Skywalker Princess Leia Organa Anakin Skywalker \\\n", "1 like like like like \n", "2 neutral neutral neutral neutral \n", "3 like like like like \n", "4 like like like like \n", "5 like like like dislike \n", "\n", " Obi Wan Kenobi Emperor Palpatine Darth Vader Lando Calrissian Boba Fett \\\n", "1 like like like neutral neutral \n", "2 neutral neutral neutral neutral neutral \n", "3 like neutral neutral neutral neutral \n", "4 like like like like dislike \n", "5 like dislike like neutral like \n", "\n", " C-3P0 R2 D2 Jar Jar Binks Padme Amidala Yoda \n", "1 like like like like like \n", "2 neutral neutral neutral neutral neutral \n", "3 neutral neutral neutral neutral neutral \n", "4 like like like like like \n", "5 like like dislike like like " ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "characters.head()" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
variablevalue
0Han Sololike
2Han Sololike
3Han Sololike
4Han Sololike
5Han Sololike
\n", "
" ], "text/plain": [ " variable value\n", "0 Han Solo like\n", "2 Han Solo like\n", "3 Han Solo like\n", "4 Han Solo like\n", "5 Han Solo like" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Unpivot the DataFrame characters from wide to long format\n", "melted = characters.melt()\n", "# excluding 'neutral' values\n", "melted = melted[melted['value']!='neutral']\n", "melted.head()" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Visualisation\n", "import matplotlib.pyplot as plt\n", "from matplotlib import colors\n", "\n", "fig,ax=plt.subplots(figsize=(12,5))\n", "\n", "# keeping only the 'like' value and group by characters\n", "like = melted[melted['value']=='like'].groupby('variable').size()\n", "# keeping only the 'dislike' value and group by characters\n", "dislike = melted[melted['value']=='dislike'].groupby('variable').size()\n", "# set the x axis ticks index\n", "ind = np.arange(1,15) \n", "# set the width of bars\n", "width = 0.35 \n", "\n", "like_bars = ax.bar(ind - width/2, like, width,label='like',color='blue')\n", "dislike_bars = ax.bar(ind + width/2 , dislike, width,label='dislike',color='orange')\n", "# set legend\n", "ax.legend(loc='upper left')\n", "# set x axis ticks labels\n", "ax.set_xticks(ind + width / 2)\n", "ax.set_xticklabels(like.index,rotation=90)\n", "# ax.set_title\n", "ax.set_title('The most controversial character in Star Wars')\n", "# remove spines\n", "for key,spine in ax.spines.items():\n", " if key in ['top','right']:\n", " spine.set_visible(False) \n", "# remove x,y Ticks\n", "ax.yaxis.set_ticks_position('none')\n", "ax.xaxis.set_ticks_position('none')\n", "# ax.tick_params(axis='x', rotation=45)\n", "# make colors in the barplot stand out for 'Jar Jar Binks' and 'Emperor Palpatine'\n", "for charac in characters.columns:\n", " if charac not in ['Jar Jar Binks','Emperor Palpatine']:\n", " pos_dislike = dislike.index.get_loc(charac)\n", " pos_like = dislike.index.get_loc(charac) \n", " like_bars.patches[pos_like].set_facecolor('#888888')\n", " dislike_bars.patches[pos_dislike].set_facecolor('#888888')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is surprising to find that 'Jar Jar Binks' is the most controversial character wich is recognized as one of the most hated characters in Star Wars !" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## Conclusion:\n", "In this project we have explored the Star Wars survey that was made by [FiveThirtyEight](https://fivethirtyeight.com/) team. We have found out the following:\n", "* In general, fans seem to prefer the original trilogy of the cinematic saga Star Wars which consists of \"A New Hope (1977)\", \"The Empire Strikes Back (1980)\" and \"Return of the Jedi (1983)\" more than the rest of the collection. \n", "* \"Star Wars: Episode V The Empire Strikes Back\" is considered by the respondents to be the best film in the saga hence it makes it the most seen Star Wars movie by the fans.\n", "* Men rated the three original movies at the top of their favorite star wars films while only two of the original movies were highly rated by women, they considered \"Episode I: The Phantom Menace 1999\" more popular than \"Episode IV: A New Hope 1977\".\n", "* Most of the Star Wars fans who responded to the survey are located in the South Atlantic states, the East North Central, the Pacific and the Middle Atlantic.\n", "* 95% of the Star Wars fans who respond to the survey have more than a High school degree.\n", "* About 50% of Star Wars fans are confident that 'Han Solo' shot first in the other hand 27% believe that 'Greedo' shot first. \n", "* It seems that the old prefer science fiction films more than the young.\n", "* 'Yoda' and 'Han Solo' are the respondents' favorite characters, in contrast 'Jar Jar Binks' is the least popular among the characters.\n", "* It is surprising to find that 'Jar Jar Binks' is the most controversial character wich is recognized as one of the most hated characters in Star Wars!" ] } ], "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": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 1 }