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imdb_data.py
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imdb_data.py
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import pandas as pd
import math
import datetime
def get_imdb_data():
with open('ratings.csv', 'r', encoding='mac_roman', newline='') as csvfile:
df = pd.read_csv(csvfile)
df = df[df['Title Type'] == 'movie'].copy()
df = df.drop('Title Type', axis=1).copy()
df['Release Date'] = pd.to_datetime(df['Release Date'])
df['Date Rated'] = pd.to_datetime(df['Date Rated'])
df['Diff in ratings'] = round(df['IMDb Rating'] - df['Your Rating'],1)
df['Link'] = '<a href=”' + df['URL'].astype(str) +'”>'+ df['Title'].astype(str)
decade_date_range = range(math.floor(df['Year'].min()/10) * 10, datetime.date.today().year + 11, 10)
decade_date_labels = [str(i) + "'s" for i in list(decade_date_range)[:len(list(decade_date_range))-1]]
df['Decade'] = pd.cut(
df['Year'],
bins=list(decade_date_range),
labels=decade_date_labels,
include_lowest=True,
right=False
)
df['genre_list'] = df['Genres'].str.split(', ')
df['Days not rated'] = (df['Date Rated'] - df['Release Date']).dt.days
return df