Star Wars Survey¶
Importing data¶
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import pandas as pd
star_wars = pd.read_csv("star_wars.csv", encoding="ISO-8859-1")
star_wars.head(10)
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Displaying column headers¶
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star_wars.columns
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Eliminating null values and renaming columns¶
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star_wars = star_wars[pd.notnull(star_wars["RespondentID"])]
yes_no = {
"Yes": True,
"No": False
}
star_wars["Have you seen any of the 6 films in the Star Wars franchise?"] = star_wars[
"Have you seen any of the 6 films in the Star Wars franchise?"].map(yes_no
)
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?"].map(yes_no
)
import numpy as np
movie_mapping = {
"Star Wars: Episode I The Phantom Menace": True,
np.nan: False,
"Star Wars: Episode II Attack of the Clones": True,
"Star Wars: Episode III Revenge of the Sith": True,
"Star Wars: Episode IV A New Hope": True,
"Star Wars: Episode V The Empire Strikes Back": True,
"Star Wars: Episode VI Return of the Jedi": True
}
for col in star_wars.columns[3:9]:
star_wars[col] = star_wars[col].map(movie_mapping)
star_wars = star_wars.rename(columns={
"Which of the following Star Wars films have you seen? Please select all that apply.": "seen_1",
"Unnamed: 4": "seen_2",
"Unnamed: 5": "seen_3",
"Unnamed: 6": "seen_4",
"Unnamed: 7": "seen_5",
"Unnamed: 8": "seen_6"
})
star_wars.head(10)
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Changing numeric data to type: float, and updating additional column names¶
In [16]:
star_wars[star_wars.columns[9:15]] = star_wars[star_wars.columns[9:15]].astype(float)
star_wars = star_wars.rename(columns={
"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.": "ranking_1",
"Unnamed: 10": "ranking_2",
"Unnamed: 11": "ranking_3",
"Unnamed: 12": "ranking_4",
"Unnamed: 13": "ranking_5",
"Unnamed: 14": "ranking_6"
})
star_wars.head(10)
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Creating bar plot for star wars movie rankings (Highest rated movies have lowest scores)¶
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%matplotlib inline
ranking_fields = star_wars.columns[9:15]
star_wars.mean()[ranking_fields].plot.bar()
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We have eliminated rows with missing data for the RespondentID column and cleaned up the first 14 columns. The best rated film is "Empire Strikes Back" and the worst is "Revenge of the Sith." I find this surprising since I thought "Phantom Menace" was the worst of the franchise.¶
Creating bar plot for which movie's were seen by survey respondants¶
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seen_fields = star_wars.columns[3:9]
star_wars.sum()[seen_fields].plot.bar()
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The seen columns appear highly correlated to the ranking columns which makes sense because more people are likely to watch better films.¶
Now we will take a look at how these bar plots look for star wars franchise fans vs. non fans¶
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sw_fan = star_wars[star_wars["Do you consider yourself to be a fan of the Star Wars film franchise?"] == True]
not_sw_fan = star_wars[star_wars["Do you consider yourself to be a fan of the Star Wars film franchise?"] == False]
Creating bar plot for rankings by star wars fans¶
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ranking_fields_sw_fan = sw_fan.columns[9:15]
sw_fan.mean()[ranking_fields_sw_fan].plot.bar()
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Creating bar plot for seen by Star Wars fans¶
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seen_fields_sw_fan = sw_fan.columns[3:9]
sw_fan.sum()[seen_fields_sw_fan].plot.bar()
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Creating bar plot for rankings by non fans¶
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ranking_fields_not_sw_fan = not_sw_fan.columns[9:15]
not_sw_fan.mean()[ranking_fields_not_sw_fan].plot.bar()
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Creating bar plot for seen by non fans¶
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seen_fields_not_sw_fan = not_sw_fan.columns[3:9]
not_sw_fan.sum()[seen_fields_not_sw_fan].plot.bar()
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