Read and format project data
# Include and execute your code here
url = "https://raw.githubusercontent.com/fivethirtyeight/data/master/star-wars-survey/StarWars.csv"
df = pd.read_csv(url, encoding='ISO-8859-1') # or try 'latin1'
# print(df.head())Elevator pitch
paste your elevator pitch here A SHORT (4-5 SENTENCES) PARAGRAPH THAT DESCRIBES KEY INSIGHTS TAKEN FROM METRICS IN THE PROJECT RESULTS THINK TOP OR MOST IMPORTANT RESULTS.
Highlight the Questions and Tasks
Client Request
The Client is who performed the survey but outsourced the analitics to a 3rd party. They want you to clean up the data so you can: a. Validate the data provided on GitHub lines up with the article by recreating 2 of the visuals from the article a. Determine if you predict if a person from the survey makes more than $50k
The Cleaning Process being performed in order to make the dataset usable.
Read and format data
# Include and execute your code here
# Remove the Second Row as it is unnecessary
df = df.iloc[1:, :]
#Rename the columns
df.columns = ['RespondentID',
'seen_any',
'sw_fan',
'seen_first',
'seen_second',
'seen_third',
'seen_fourth',
'seen_fifth',
'seen_sixth',
'rank_1',
'rank_2',
'rank_3',
'rank_4',
'rank_5',
'rank_6',
'Han_Solo',
'Luke_Skywalker',
'Leia_Organa',
'Anakin_Skywalker',
'Obi_Wan_Kenobi',
'Emperor_Palpatine',
'Darth_Vader',
'Lando_Calrissian',
'Boba_Fett',
'C-3P0',
'R2_D2',
'Jar_Jar_Binks',
'Padme_Amidala',
'Yoda',
'shot_first',
'knows_expand_universe',
'fan_expand_universe',
'star_trek_fan',
'gender',
'age',
'income',
'education',
'region'
]
# Define Boolean Conversion Function
def to_bool(cell):
return int(
bool(
str(
cell
).strip()
)
)
# Columns to Convert
bool_columns = [
'sw_fan',
'star_trek_fan',
'seen_first',
'seen_second',
'seen_third',
'seen_fourth',
'seen_fifth',
'seen_sixth',
'knows_expand_universe',
'fan_expand_universe'
]
# Convert Columns
for col in bool_columns:
df[col + '_bool'] = df[col].apply(to_bool)
# Create
print(df.head()) RespondentID seen_any sw_fan seen_first \
1 3.292880e+09 Yes Yes Star Wars: Episode I The Phantom Menace
2 3.292880e+09 No NaN NaN
3 3.292765e+09 Yes No Star Wars: Episode I The Phantom Menace
4 3.292763e+09 Yes Yes Star Wars: Episode I The Phantom Menace
5 3.292731e+09 Yes Yes Star Wars: Episode I The Phantom Menace
seen_second \
1 Star Wars: Episode II Attack of the Clones
2 NaN
3 Star Wars: Episode II Attack of the Clones
4 Star Wars: Episode II Attack of the Clones
5 Star Wars: Episode II Attack of the Clones
seen_third \
1 Star Wars: Episode III Revenge of the Sith
2 NaN
3 Star Wars: Episode III Revenge of the Sith
4 Star Wars: Episode III Revenge of the Sith
5 Star Wars: Episode III Revenge of the Sith
seen_fourth \
1 Star Wars: Episode IV A New Hope
2 NaN
3 NaN
4 Star Wars: Episode IV A New Hope
5 Star Wars: Episode IV A New Hope
seen_fifth \
1 Star Wars: Episode V The Empire Strikes Back
2 NaN
3 NaN
4 Star Wars: Episode V The Empire Strikes Back
5 Star Wars: Episode V The Empire Strikes Back
seen_sixth rank_1 ... sw_fan_bool \
1 Star Wars: Episode VI Return of the Jedi 3 ... 1
2 NaN NaN ... 1
3 NaN 1 ... 1
4 Star Wars: Episode VI Return of the Jedi 5 ... 1
5 Star Wars: Episode VI Return of the Jedi 5 ... 1
star_trek_fan_bool seen_first_bool seen_second_bool seen_third_bool \
1 1 1 1 1
2 1 1 1 1
3 1 1 1 1
4 1 1 1 1
5 1 1 1 1
seen_fourth_bool seen_fifth_bool seen_sixth_bool knows_expand_universe_bool \
1 1 1 1 1
2 1 1 1 1
3 1 1 1 1
4 1 1 1 1
5 1 1 1 1
fan_expand_universe_bool
1 1
2 1
3 1
4 1
5 1
[5 rows x 48 columns]include figures in chunks and discuss your findings in the figure.
plot example
# Include and execute your code heretable example
# Include and execute your code here