Netflix! What started in 1997 as a DVD rental service has since exploded into one of the largest entertainment and media companies.
Given the large number of movies and series available on the platform, it is a perfect opportunity to flex your exploratory data analysis skills and dive into the entertainment industry.
You work for a production company that specializes in nostalgic styles. You want to do some research on movies released in the 1990's. You'll delve into Netflix data and perform exploratory data analysis to better understand this awesome movie decade!
You have been supplied with the dataset netflix_data.csv
, along with the following table detailing the column names and descriptions. Feel free to experiment further after submitting!
The data
netflix_data.csv
Column | Description |
---|---|
show_id | The ID of the show |
type | Type of show |
title | Title of the show |
director | Director of the show |
cast | Cast of the show |
country | Country of origin |
date_added | Date added to Netflix |
release_year | Year of Netflix release |
duration | Duration of the show in minutes |
description | Description of the show |
genre | Show genre |
# Importing pandas and matplotlib
import pandas as pd
import matplotlib.pyplot as plt
# Read in the Netflix CSV as a DataFrame
netflix_df = pd.read_csv("netflix_data.csv")
# Start coding here! Use as many cells as you like
import pandas as pd
netflix_df = pd.read_csv("netflix_data.csv")
netflix_df
print(netflix_df[netflix_df["type"] == 'Movie'])
Dataframe_Movies = netflix_df[netflix_df["type"] == 'Movie']
Movies_in_1990s = netflix_df[(netflix_df["release_year"] >= 1990) & (netflix_df["release_year"] <= 1999)]
Movies_in_1990s
import matplotlib.pyplot as plt
# Plotting the histogram
plt.hist(Movies_in_1990s['duration'], bins=20)
# Adding labels to the axes
plt.xlabel('Duration')
plt.ylabel('Movies')
# Display the plot
plt.show()
# Finding the most frequent movie duration in the 1990s
most_frequent_duration = Movies_in_1990s['duration'].mode()[0]
# Saving the result as an integer
duration = int(most_frequent_duration)
# Display the result
duration
short_movies = Movies_in_1990s[Movies_in_1990s['duration'] <= 90]
short_movies
short_movies = short_movies[short_movies['genre'] == 'Action']
short_movies
short_action_movie = short_movies['genre'].mode()[0]
# Counting the number of short action movies
short_movie_count = short_movies[short_movies['genre'] == short_action_movie].shape[0]
# Display the result
short_movie_count