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 |
## What was the most frequent movie duration in the 1990s? ##
# 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")
# Variáveis de duração e ano do filme
movie_duration = netflix_df.iloc[:, 8]
release_year = netflix_df.iloc[:, 7]
# Filtrar filmes dos anos 90
movies_90s = netflix_df[(release_year >= 1990) & (release_year < 2000)]
# Imprimir a duração dos filmes dos anos 90
#print(movies_90s[["title", "duration", "release_year"]])
# What was the most frequent movie duration in the 1990s?
duration = int(movies_90s['duration'].mode())
print(duration)
#Histogram mostrando durações mais frequentes de filmes
plt.hist(movies_90s["duration"],bins=20)
#Personalização do Histograma
xlab = 'Movie duration in minutes'
ylab = 'Movies'
title = 'Most frequent movie duration in the 1990s'
#Apply
plt.xlabel(xlab)
plt.ylabel(ylab)
plt.title(title)
#Custom ticks
plt.xticks ([0,20,40,60,80,100,120,140,160,180,200])
#Show plot
plt.show ()## Number of short action movies released in the 1990s ##
# 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")
# Variáveis de duração e ano do filme
movie_duration = netflix_df.iloc[:, 8]
release_year = netflix_df.iloc[:, 7]
genre = netflix_df.iloc[:, -1]
# Filtrar filmes dos anos 90 curtos
short_90s_movies = netflix_df[(release_year >= 1990) & (release_year < 2000) & (movie_duration < 90) & (genre == 'Action')]
#Count filmes curtos dos anos 90
short_movie_count = short_90s_movies.shape[0]
print(short_movie_count)