{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "IPython.OutputArea.prototype._should_scroll = function(lines) {\n", " return false;\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%%javascript\n", "IPython.OutputArea.prototype._should_scroll = function(lines) {\n", " return false;\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Let's Clean Some Data\n", "\n", "Fivethirtyeight has some great data sets and this is one of them. In July 2014, before the third Star Wars trilogy was released, they decided to survey Americans to see which of the first six movies was their favorite. Let's take a look at the results. Some light cleaning should make it more usable!" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": false }, "outputs": [], "source": [ "# import libraries and csv\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "star_wars = pd.read_csv(\"star_wars.csv\", encoding=\"ISO-8859-1\")" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": false }, "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?Do you consider yourself to be a fan of the Star Trek franchise?GenderAgeHousehold IncomeEducationLocation (Census Region)
03292879998YesYesStar 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 Jedi3.0...Very favorablyI don't understand this questionYesNoNoMale18-29NaNHigh school degreeSouth Atlantic
13292879538NoNaNNaNNaNNaNNaNNaNNaNNaN...NaNNaNNaNNaNYesMale18-29$0 - $24,999Bachelor degreeWest South Central
23292765271YesNoStar Wars: Episode I The Phantom MenaceStar Wars: Episode II Attack of the ClonesStar Wars: Episode III Revenge of the SithNaNNaNNaN1.0...Unfamiliar (N/A)I don't understand this questionNoNaNNoMale18-29$0 - $24,999High school degreeWest North Central
33292763116YesYesStar 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 Jedi5.0...Very favorablyI don't understand this questionNoNaNYesMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
43292731220YesYesStar 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 Jedi5.0...Somewhat favorablyGreedoYesNoNoMale18-29$100,000 - $149,999Some college or Associate degreeWest North Central
53292719380YesYesStar 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 Jedi1.0...Very favorablyHanYesNoYesMale18-29$25,000 - $49,999Bachelor degreeMiddle Atlantic
63292684787YesYesStar 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 Jedi6.0...Very favorablyHanYesNoNoMale18-29NaNHigh school degreeEast North Central
73292663732YesYesStar 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 Jedi4.0...Very favorablyHanNoNaNYesMale18-29NaNHigh school degreeSouth Atlantic
83292654043YesYesStar 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 Jedi5.0...Somewhat favorablyHanNoNaNNoMale18-29$0 - $24,999Some college or Associate degreeSouth Atlantic
93292640424YesNoNaNStar Wars: Episode II Attack of the ClonesNaNNaNNaNNaN1.0...Very favorablyI don't understand this questionNoNaNNoMale18-29$25,000 - $49,999Some college or Associate degreePacific
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" ], "text/plain": [ " RespondentID Have you seen any of the 6 films in the Star Wars franchise? \\\n", "0 3292879998 Yes \n", "1 3292879538 No \n", "2 3292765271 Yes \n", "3 3292763116 Yes \n", "4 3292731220 Yes \n", "5 3292719380 Yes \n", "6 3292684787 Yes \n", "7 3292663732 Yes \n", "8 3292654043 Yes \n", "9 3292640424 Yes \n", "\n", " Do you consider yourself to be a fan of the Star Wars film franchise? \\\n", "0 Yes \n", "1 NaN \n", "2 No \n", "3 Yes \n", "4 Yes \n", "5 Yes \n", "6 Yes \n", "7 Yes \n", "8 Yes \n", "9 No \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 NaN \n", "2 Star Wars: Episode I The Phantom Menace \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 NaN \n", "\n", " Unnamed: 4 \\\n", "0 Star Wars: Episode II Attack of the Clones \n", "1 NaN \n", "2 Star Wars: Episode II Attack of the Clones \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 NaN \n", "2 Star Wars: Episode III Revenge of the Sith \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 NaN \n", "\n", " Unnamed: 6 \\\n", "0 Star Wars: Episode IV A New Hope \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode IV A New Hope \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 NaN \n", "\n", " Unnamed: 7 \\\n", "0 Star Wars: Episode V The Empire Strikes Back \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode V The Empire Strikes Back \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 NaN \n", "\n", " Unnamed: 8 \\\n", "0 Star Wars: Episode VI Return of the Jedi \n", "1 NaN \n", "2 NaN \n", "3 Star Wars: Episode VI Return of the Jedi \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 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. \\\n", "0 3.0 \n", "1 NaN \n", "2 1.0 \n", "3 5.0 \n", "4 5.0 \n", "5 1.0 \n", "6 6.0 \n", "7 4.0 \n", "8 5.0 \n", "9 1.0 \n", "\n", " ... Unnamed: 28 Which character shot first? \\\n", "0 ... Very favorably I don't understand this question \n", "1 ... NaN NaN \n", "2 ... Unfamiliar (N/A) I don't understand this question \n", "3 ... Very favorably I don't understand this question \n", "4 ... Somewhat favorably Greedo \n", "5 ... Very favorably Han \n", "6 ... Very favorably Han \n", "7 ... Very favorably Han \n", "8 ... Somewhat favorably Han \n", "9 ... Very favorably I don't understand this question \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "0 Yes \n", "1 NaN \n", "2 No \n", "3 No \n", "4 Yes \n", "5 Yes \n", "6 Yes \n", "7 No \n", "8 No \n", "9 No \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe? \\\n", "0 No \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 No \n", "5 No \n", "6 No \n", "7 NaN \n", "8 NaN \n", "9 NaN \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? Gender \\\n", "0 No Male \n", "1 Yes Male \n", "2 No Male \n", "3 Yes Male \n", "4 No Male \n", "5 Yes Male \n", "6 No Male \n", "7 Yes Male \n", "8 No Male \n", "9 No Male \n", "\n", " Age Household Income Education \\\n", "0 18-29 NaN High school degree \n", "1 18-29 $0 - $24,999 Bachelor degree \n", "2 18-29 $0 - $24,999 High school degree \n", "3 18-29 $100,000 - $149,999 Some college or Associate degree \n", "4 18-29 $100,000 - $149,999 Some college or Associate degree \n", "5 18-29 $25,000 - $49,999 Bachelor degree \n", "6 18-29 NaN High school degree \n", "7 18-29 NaN High school degree \n", "8 18-29 $0 - $24,999 Some college or Associate degree \n", "9 18-29 $25,000 - $49,999 Some college or Associate degree \n", "\n", " Location (Census Region) \n", "0 South Atlantic \n", "1 West South Central \n", "2 West North Central \n", "3 West North Central \n", "4 West North Central \n", "5 Middle Atlantic \n", "6 East North Central \n", "7 South Atlantic \n", "8 South Atlantic \n", "9 Pacific \n", "\n", "[10 rows x 38 columns]" ] }, "metadata": {}, "output_type": "display_data" }, { "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?',\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')" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "(1186, 38)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# explore the data frame\n", "display(star_wars.head(10))\n", "display(star_wars.columns)\n", "display(star_wars.shape)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# rename columns\n", "new_columns = {\"Have you seen any of the 6 films in the Star Wars franchise?\":\"Seen any of the first 6 Star Wars movies?\",\n", " \"Do you consider yourself to be a fan of the Star Wars film franchise?\":\"Fan of the Star Wars franchise?\",\n", " \"Which of the following Star Wars films have you seen? Please select all that apply.\" : \"seen_ep_1\",\n", " \"Unnamed: 4\" : \"seen_ep_2\",\n", " \"Unnamed: 5\" : \"seen_ep_3\",\n", " \"Unnamed: 6\" : \"seen_ep_4\",\n", " \"Unnamed: 7\" : \"seen_ep_5\",\n", " \"Unnamed: 8\" : \"seen_ep_6\",\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.\":\"rank_ep_1\",\n", " \"Unnamed: 10\":\"rank_ep_2\",\n", " \"Unnamed: 11\":\"rank_ep_3\",\n", " \"Unnamed: 12\":\"rank_ep_4\",\n", " \"Unnamed: 13\":\"rank_ep_5\",\n", " \"Unnamed: 14\":\"rank_ep_6\"}\n", "\n", "star_wars = star_wars.rename(columns = new_columns)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Yes 936\n", "No 250\n", "Name: Seen any of the first 6 Star Wars movies?, dtype: int64\n", "Yes 552\n", "NaN 350\n", "No 284\n", "Name: Fan of the Star Wars franchise?, dtype: int64\n", "Star Wars: Episode I The Phantom Menace 673\n", "NaN 513\n", "Name: seen_ep_1, dtype: int64\n" ] } ], "source": [ "# value counts for columns 1:3\n", "print(star_wars[\"Seen any of the first 6 Star Wars movies?\"].value_counts(dropna=False))\n", "print(star_wars[\"Fan of the Star Wars franchise?\"].value_counts(dropna=False))\n", "print(star_wars[\"seen_ep_1\"].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True 936\n", "False 250\n", "Name: Seen any of the first 6 Star Wars movies?, dtype: int64\n", "True 552\n", "NaN 350\n", "False 284\n", "Name: Fan of the Star Wars franchise?, dtype: int64\n" ] }, { "data": { "text/plain": [ "True 673\n", "False 513\n", "Name: seen_ep_1, dtype: int64" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# switch values to boolean for columns 1:2\n", "yes_no_bool = {\"Yes\":True, \"No\":False}\n", "star_wars[\"Seen any of the first 6 Star Wars movies?\"] = star_wars[\"Seen any of the first 6 Star Wars movies?\"].map(yes_no_bool)\n", "star_wars[\"Fan of the Star Wars franchise?\"] = star_wars[\"Fan of the Star Wars franchise?\"].map(yes_no_bool)\n", "\n", "\n", "# switch values to boolean for columns 3:9\n", "watch_bool = {\"Star Wars: Episode I The Phantom Menace\" : True,\n", " \"Star Wars: Episode II Attack of the Clones\" : True,\n", " \"Star Wars: Episode III Revenge of the Sith\" : True,\n", " \"Star Wars: Episode IV A New Hope\" : True,\n", " \"Star Wars: Episode V The Empire Strikes Back\" : True,\n", " \"Star Wars: Episode VI Return of the Jedi\" : True,\n", " np.NaN : False}\n", "\n", "for col in star_wars.columns[3:9]:\n", " star_wars[col] = star_wars[col].map(watch_bool)\n", "\n", "# value counts for columns 1:3\n", "print(star_wars[\"Seen any of the first 6 Star Wars movies?\"].value_counts(dropna=False))\n", "print(star_wars[\"Fan of the Star Wars franchise?\"].value_counts(dropna=False))\n", "display(star_wars.iloc[:,3].value_counts(dropna=False))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dtype('float64')" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# convert rankings to float\n", "star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)\n", "\n", "# star_wars.columns[9].dtype # why does this work sometimes?\n", "star_wars.iloc[:,9].dtype" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Closer Look\n", "Now that the columns are renamed and the values have been changed to True/False we can start analyzing the data." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Seen any of the first 6 Star Wars movies? 0.789207\n", "Fan of the Star Wars franchise? 0.660287\n", "seen_ep_1 0.567454\n", "seen_ep_2 0.481450\n", "seen_ep_3 0.463744\n", "seen_ep_4 0.511804\n", "seen_ep_5 0.639123\n", "seen_ep_6 0.622260\n", "rank_ep_1 3.732934\n", "rank_ep_2 4.087321\n", "rank_ep_3 4.341317\n", "rank_ep_4 3.272727\n", "rank_ep_5 2.513158\n", "rank_ep_6 3.047847\n", "dtype: float64" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "Seen any of the first 6 Star Wars movies? 936\n", "Fan of the Star Wars franchise? 552\n", "seen_ep_1 673\n", "seen_ep_2 571\n", "seen_ep_3 550\n", "seen_ep_4 607\n", "seen_ep_5 758\n", "seen_ep_6 738\n", "dtype: object" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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RespondentIDSeen any of the first 6 Star Wars movies?seen_ep_1seen_ep_2seen_ep_3seen_ep_4seen_ep_5seen_ep_6rank_ep_1rank_ep_2rank_ep_3rank_ep_4rank_ep_5rank_ep_6
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Male3.290478e+090.8511070.7263580.6498990.6378270.6881290.7887320.7786724.0378254.2245864.2748822.9976362.4586293.002364
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RespondentIDSeen any of the first 6 Star Wars movies?seen_ep_1seen_ep_2seen_ep_3seen_ep_4seen_ep_5seen_ep_6
Gender
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" ], "text/plain": [ " RespondentID Seen any of the first 6 Star Wars movies? seen_ep_1 \\\n", "Gender \n", "Female 1806109676556 397 298 \n", "Male 1635367528067 423 361 \n", "\n", " seen_ep_2 seen_ep_3 seen_ep_4 seen_ep_5 seen_ep_6 \n", "Gender \n", "Female 237 222 255 353 338 \n", "Male 323 317 342 392 387 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get average value for seen any, fan, which episode, rankings by episode\n", "group_means = star_wars.iloc[:,1:15].mean()\n", "display(group_means)\n", "\n", "# totals\n", "group_sums = star_wars.iloc[:,1:9].sum()\n", "display(group_sums)\n", "\n", "gender_means = star_wars.groupby(\"Gender\").mean()\n", "display(gender_means)\n", "\n", "gender_sums = star_wars.groupby(\"Gender\").sum()\n", "gender_sums = gender_sums.iloc[:,0:8]\n", "gender_sums" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True 936\n", "False 250\n", "Name: Seen any of the first 6 Star Wars movies?, dtype: int64" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "True 552\n", "NaN 350\n", "False 284\n", "Name: Fan of the Star Wars franchise?, dtype: int64" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "0.6602870813397129" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# math check :)\n", "display(star_wars[\"Seen any of the first 6 Star Wars movies?\"].value_counts(dropna=False))\n", "\n", "display(star_wars[\"Fan of the Star Wars franchise?\"].value_counts(dropna=False))\n", "display(552/(552+284))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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RespondentIDSeen any of the first 6 Star Wars movies?Fan of the Star Wars franchise?seen_ep_1seen_ep_2seen_ep_3seen_ep_4seen_ep_5seen_ep_6rank_ep_1...Unnamed: 28Which character shot first?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?GenderAgeHousehold IncomeEducationLocation (Census Region)
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803291669388TrueNaNFalseFalseFalseFalseFalseFalseNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
963291570206TrueNaNFalseFalseFalseFalseFalseFalseNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1053291469991TrueNaNFalseFalseFalseFalseFalseFalseNaN...NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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" ], "text/plain": [ " RespondentID Seen any of the first 6 Star Wars movies? \\\n", "10 3292637870 True \n", "80 3291669388 True \n", "96 3291570206 True \n", "105 3291469991 True \n", "127 3291420030 True \n", "\n", " Fan of the Star Wars franchise? seen_ep_1 seen_ep_2 seen_ep_3 \\\n", "10 NaN False False False \n", "80 NaN False False False \n", "96 NaN False False False \n", "105 NaN False False False \n", "127 NaN False False False \n", "\n", " seen_ep_4 seen_ep_5 seen_ep_6 rank_ep_1 ... Unnamed: 28 \\\n", "10 False False False NaN ... NaN \n", "80 False False False NaN ... NaN \n", "96 False False False NaN ... NaN \n", "105 False False False NaN ... NaN \n", "127 False False False NaN ... NaN \n", "\n", " Which character shot first? \\\n", "10 NaN \n", "80 NaN \n", "96 NaN \n", "105 NaN \n", "127 NaN \n", "\n", " Are you familiar with the Expanded Universe? \\\n", "10 NaN \n", "80 NaN \n", "96 NaN \n", "105 NaN \n", "127 NaN \n", "\n", " Do you consider yourself to be a fan of the Expanded Universe? \\\n", "10 NaN \n", "80 NaN \n", "96 NaN \n", "105 NaN \n", "127 NaN \n", "\n", " Do you consider yourself to be a fan of the Star Trek franchise? Gender \\\n", "10 NaN NaN \n", "80 NaN NaN \n", "96 NaN NaN \n", "105 NaN NaN \n", "127 NaN NaN \n", "\n", " Age Household Income Education Location (Census Region) \n", "10 NaN NaN NaN NaN \n", "80 NaN NaN NaN NaN \n", "96 NaN NaN NaN NaN \n", "105 NaN NaN NaN NaN \n", "127 NaN NaN NaN NaN \n", "\n", "[5 rows x 38 columns]" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "(100, 38)" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# fan_nan\n", "fan_nan = star_wars[(star_wars.iloc[:,1] == True) & (star_wars.iloc[:,2].isna())]\n", "display(fan_nan.head())\n", "display(fan_nan.shape)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# female, group, and male % seen and total seen compared to rank (1 is good!)\n", "ep_index = [\"Ep 1\",\"Ep 2\",\"Ep 3\",\"Ep 4\",\"Ep 5\",\"Ep 6\"]\n", "\n", "# % seen and rank\n", "fig = plt.figure(figsize=(18,5))\n", "ax = fig.add_subplot(131) # female % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "gender_means.iloc[0,2:8].plot(kind=\"bar\", color=\"#BD8D1E\", ax=ax, width=width, position=1)\n", "gender_means.iloc[0,8:14].plot(kind=\"bar\", color=\"#B3592D\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Female % Seen & Rank\", size=15)\n", "ax = fig.add_subplot(132) # group % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "group_means.iloc[2:8].plot(kind=\"bar\", color=\"#4393C4\", ax=ax, width=width, position=1)\n", "group_means.iloc[8:14].plot(kind=\"bar\", color=\"#126AA1\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Group % Seen & Rank\", size=15)\n", "ax = fig.add_subplot(133)# male % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "gender_means.iloc[1,2:8].plot(kind=\"bar\", color=\"#5FC295\", ax=ax, width=width, position=1)\n", "gender_means.iloc[1,8:14].plot(kind=\"bar\", color=\"#116B43\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Male % Seen & Rank\", size=15)\n", "plt.show()\n", "\n", "# sums and rank\n", "fig = plt.figure(figsize=(18,5))\n", "ax = fig.add_subplot(131) # female total seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "gender_sums.iloc[0,2:8].plot(kind=\"bar\", color=\"#F7CC65\", ax=ax, width=width, position=1)\n", "gender_means.iloc[0,8:14].plot(kind=\"bar\", color=\"#B3592D\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Female Total & Rank\", size=15)\n", "ax = fig.add_subplot(132) # group total seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "group_sums.iloc[2:8].plot(kind=\"bar\", color=\"#75BEEB\", ax=ax, width=width, position=1)\n", "group_means.iloc[8:14].plot(kind=\"bar\", color=\"#126AA1\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Group Total & Rank\", size=15)\n", "ax = fig.add_subplot(133) # male total seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "gender_sums.iloc[1,2:8].plot(kind=\"bar\", color=\"#B0F7D7\", ax=ax, width=width, position=1)\n", "gender_means.iloc[1,8:14].plot(kind=\"bar\", color=\"#116B43\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Male Total & Rank\", size=15)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Impressions\n", "* The original dataset contains 1186 rows of unique respondents. 78% of them have seen a Star Wars movie and 66% consider themselves fans of the franchise. That's pretty good!\n", "\n", "* There are 100 respondents who have seen some of the movies but their answer to if they were a fan is set to `NaN`. This sets all the other values in the row to `NaN` as well. There's no indication as to why they are blank.\n", "\n", "* The bar charts show a pretty even distribution of which movies the respondents have seen. The most seen are Episodes V, VI, and I respectively.\n", "\n", "* The favorite is Episode V, with VI and IV coming in close second and third ranks. Episodes II and III are not popular...\n", "\n", "* There doesn't seem to be a big difference between the entire group and either gender.\n", "\n", "* Using the total number seen or percentage of the total seen doesn't look much different on the graph. The rest of the analysis will use percentages." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Other Groups\n", "There are other demographic groups available. Next we'll compare Star Trek fans, age, income, education and geographic region." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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RespondentIDSeen any of the first 6 Star Wars movies?seen_ep_1seen_ep_2seen_ep_3seen_ep_4seen_ep_5seen_ep_6rank_ep_1rank_ep_2rank_ep_3rank_ep_4rank_ep_5rank_ep_6
Do you consider yourself to be a fan of the Star Trek franchise?
No3.290120e+090.6443060.4695790.3556940.3447740.4024960.5507020.5210613.4878643.9152544.2784503.4334142.6343833.244552
Yes3.290126e+090.9718970.8524590.7868850.7540980.8009370.9297420.9274003.9686754.2554224.4033823.1108432.4072292.850602
\n", "
" ], "text/plain": [ " RespondentID \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 3.290120e+09 \n", "Yes 3.290126e+09 \n", "\n", " Seen any of the first 6 Star Wars movies? \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 0.644306 \n", "Yes 0.971897 \n", "\n", " seen_ep_1 seen_ep_2 \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 0.469579 0.355694 \n", "Yes 0.852459 0.786885 \n", "\n", " seen_ep_3 seen_ep_4 \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 0.344774 0.402496 \n", "Yes 0.754098 0.800937 \n", "\n", " seen_ep_5 seen_ep_6 \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 0.550702 0.521061 \n", "Yes 0.929742 0.927400 \n", "\n", " rank_ep_1 rank_ep_2 \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 3.487864 3.915254 \n", "Yes 3.968675 4.255422 \n", "\n", " rank_ep_3 rank_ep_4 \\\n", "Do you consider yourself to be a fan of the Sta... \n", "No 4.278450 3.433414 \n", "Yes 4.403382 3.110843 \n", "\n", " rank_ep_5 rank_ep_6 \n", "Do you consider yourself to be a fan of the Sta... \n", "No 2.634383 3.244552 \n", "Yes 2.407229 2.850602 " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# trekkies\n", "trekkies = star_wars.groupby(star_wars.iloc[:,32]).mean()\n", "trekkies" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# % seen and rank\n", "fig = plt.figure(figsize=(18,5))\n", "ax = fig.add_subplot(131)# Star Trek liker % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "trekkies.iloc[1,2:8].plot(kind=\"bar\", color=\"#F2A679\", ax=ax, width=width, position=1)\n", "trekkies.iloc[1,8:14].plot(kind=\"bar\", color=\"#61514C\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Star Trek liker % Seen & Rank\", size=15)\n", "ax = fig.add_subplot(132) # group % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "group_means.iloc[2:8].plot(kind=\"bar\", color=\"#4393C4\", ax=ax, width=width, position=1)\n", "group_means.iloc[8:14].plot(kind=\"bar\", color=\"#126AA1\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Group % Seen & Rank\", size=15)\n", "ax = fig.add_subplot(133) # Star Trek dis-liker % seen and average rank\n", "ax2 = ax.twinx() \n", "width = 0.4\n", "trekkies.iloc[0,2:8].plot(kind=\"bar\", color=\"#A1C4BB\", ax=ax, width=width, position=1)\n", "trekkies.iloc[0,8:14].plot(kind=\"bar\", color=\"#498271\", ax=ax2, width=width, position=0)\n", "ax.set_xticks([0,1,2,3,4,5])\n", "ax.set_xticklabels(ep_index)\n", "plt.title(\"Star Trek dis-liker % Seen & Rank\", size=15)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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RespondentIDSeen any of the first 6 Star Wars movies?seen_ep_1seen_ep_2seen_ep_3seen_ep_4seen_ep_5seen_ep_6rank_ep_1rank_ep_2rank_ep_3rank_ep_4rank_ep_5rank_ep_6
Age
18-293.290464e+090.8256880.7339450.6788990.6651380.6972480.7339450.7339454.1000004.1000003.9666672.9944442.7222223.116667
30-443.290218e+090.7723880.6529850.5895520.5671640.6567160.7350750.7350754.3478264.3091794.4757282.9323672.2125602.714976
45-603.289923e+090.8247420.6219930.5085910.4879730.5670100.7560140.7216493.5416674.1708334.5375003.3083332.4375003.004167
> 603.290001e+090.7174720.5315990.3940520.3717470.3866170.6245350.5873613.0104173.7616584.3160623.8082902.7305703.357513
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" ], "text/plain": [ " RespondentID Seen any of the first 6 Star Wars movies? seen_ep_1 \\\n", "Age \n", "18-29 3.290464e+09 0.825688 0.733945 \n", "30-44 3.290218e+09 0.772388 0.652985 \n", "45-60 3.289923e+09 0.824742 0.621993 \n", "> 60 3.290001e+09 0.717472 0.531599 \n", "\n", " seen_ep_2 seen_ep_3 seen_ep_4 seen_ep_5 seen_ep_6 rank_ep_1 \\\n", "Age \n", "18-29 0.678899 0.665138 0.697248 0.733945 0.733945 4.100000 \n", "30-44 0.589552 0.567164 0.656716 0.735075 0.735075 4.347826 \n", "45-60 0.508591 0.487973 0.567010 0.756014 0.721649 3.541667 \n", "> 60 0.394052 0.371747 0.386617 0.624535 0.587361 3.010417 \n", "\n", " rank_ep_2 rank_ep_3 rank_ep_4 rank_ep_5 rank_ep_6 \n", "Age \n", "18-29 4.100000 3.966667 2.994444 2.722222 3.116667 \n", "30-44 4.309179 4.475728 2.932367 2.212560 2.714976 \n", "45-60 4.170833 4.537500 3.308333 2.437500 3.004167 \n", "> 60 3.761658 4.316062 3.808290 2.730570 3.357513 " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# trekkies\n", "age_groups = star_wars.groupby(\"Age\").mean()\n", "age_groups" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.7" } }, "nbformat": 4, "nbformat_minor": 1 }