# import libs import pandas as pd import numpy as np import matplotlib.pyplot as plt # read in dataset star_wars_df = pd.read_csv("StarWars.csv", encoding="ISO-8859-1") # drop null values from RespondentID star_wars_df = star_wars_df.dropna(subset=["RespondentID"]) # print summary info star_wars_df.describe(include="all")

# drop unneeded columns star_wars_df = star_wars_df.drop(star_wars_df.columns[15:33] ,axis=1)

# convert the columns to True/False booleans for col in ['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?']: star_wars_df[col] = star_wars_df[col].map({ "Yes": True, "No": False })

# iterate over the marked columns for count, col in enumerate(star_wars_df.columns[3:9], start=1): # if the value is a string holding the movie name, return True, otherwise return False star_wars_df[col] = star_wars_df[col].apply(lambda x: True if isinstance(x, str) else False) # rename the column star_wars_df = star_wars_df.rename(columns={col: f"seen_movie_{count}"})

# iterate over marked column for count, col in enumerate(star_wars_df.columns[9:15], start=1): # convert column to float type star_wars_df[col] = star_wars_df[col].astype(float) # rename the column star_wars_df = star_wars_df.rename(columns={col: f"ranking_movie_{count}"})

fans_df = star_wars_df[star_wars_df["Do you consider yourself to be a fan of the Star Wars film franchise?"] == True]

# create bar chart with ranked movies ax = fans_df.loc[:, "ranking_movie_1":"ranking_movie_6"].mean().plot(kind="bar", figsize=(10, 5)) # set labels and title ax.set_xlabel("Movie") ax.set_ylabel("Ranking") plt.title("Best Ranking Movies Among Fans") # show plot plt.show()

# create bar chart with most seen movies ax = fans_df.loc[:, "seen_movie_1":"seen_movie_6"].sum().plot(kind="bar", figsize=(10, 5)) # set labels and title ax.set_xlabel("Movie") ax.set_ylabel("Count") plt.title("Most Viewed Movies") # show plot plt.show()