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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

ColumnDescription
show_idThe ID of the show
typeType of show
titleTitle of the show
directorDirector of the show
castCast of the show
countryCountry of origin
date_addedDate added to Netflix
release_yearYear of Netflix release
durationDuration of the show in minutes
descriptionDescription of the show
genreShow 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")
print(netflix_df)
# Start coding here! Use as many cells as you 

# Filtrar solo películas de la década de los 90s (1990-1999)
movies_90s = netflix_df[(netflix_df['release_year'] >= 1990) & (netflix_df['release_year'] < 2000)]

# Encontrar la duración de película más frecuente en los 90s
duration = movies_90s['duration'].mode()[0]  # Moda de la duración

# Contar películas de acción que duran menos de 90 minutos en los 90s
short_movie_count = movies_90s[(movies_90s['duration'] < 90) & (movies_90s['genre'] == "Action")].shape[0]

# Imprimir los resultados
print("Duración de película más frecuente en los 90s:", duration)
print("Número de películas de acción cortas en los 90s:", short_movie_count)

# Histograma para visualizar la distribución de duraciones
plt.hist(movies_90s['duration'], bins=15, edgecolor='black')
plt.xlabel("Duración (min)")
plt.ylabel("Frecuencia")
plt.title("Distribución de duración de películas en los 90s")
plt.show()