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 likeExploratory Data Analysis
netflix_df.columnsFirst we will filter the data for movies released in the 1990s
new_netflix_df = netflix_df[(netflix_df['release_year'] >= 1990) & (netflix_df['release_year'] <= 1999)]new_netflix_df.head()Checking if there are values that are not included in the filter
print(new_netflix_df['release_year'].value_counts())plt.hist(x=new_netflix_df['duration'])
plt.xlabel('Duration')
plt.ylabel('Frequency')
plt.show()We will then be using mode() function, as this returns the most frequent value for the specified column. As this function returns all the values, we will then use [0] to return the top most value.
duration = new_netflix_df['duration'].mode()[0]
durationOn the third task, we will count the number of short action movies from the 1990s