Python-Project

Investigating Netflix Movies and Guest Stars in The Office

Create the years and durations lists

years = [2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020] durations = [103, 101, 99, 100, 100, 95, 95, 96, 93, 90]

Create a dictionary with the two lists

movie_dict = { "years" : years, "durations": durations }

Print the dictionary

movie_dict

Import pandas under its usual alias

import pandas as pd

Create a DataFrame from the dictionary

durations_df = pd.DataFrame(movie_dict)

Print the DataFrame

print((durations_df.head))

Import matplotlib.pyplot under its usual alias and create a figure

import matplotlib.pyplot as plt fig = plt.figure()

Draw a line plot of release_years and durations

plt.plot(durations_df["years"],durations_df["durations"]) plt.xlabel("Release Years") plt.ylabel("Durations")

Create a title

plt.title("Netflix Movie Durations 2011-2020")

Show the plot

plt.show()

Read in the CSV as a DataFrame

netflix_df = pd.read_csv("datasets/netflix_data.csv")

Print the first five rows of the DataFrame

print(netflix_df.head())

Subset the DataFrame for type "Movie"

netflix_df_movies_only = netflix_df[netflix_df["type"] == "Movie"]

Select only the columns of interest

netflix_movies_col_subset = netflix_df_movies_only[["title", "country", "genre", "release_year","duration"]]

Print the first five rows of the new DataFrame

print(netflix_movies_col_subset.head())

Create a figure and increase the figure size

fig = plt.figure(figsize=(12,8))

Create a scatter plot of duration versus year

plt.scatter(netflix_movies_col_subset["release_year"],netflix_movies_col_subset["duration"]) plt.xlabel("Release Year") plt.ylabel("Duration")

Create a title

plt.title("Movie Duration by Year of Release")

Show the plot

plt.show()

Filter for durations shorter than 60 minutes

short_movies = netflix_movies_col_subset[netflix_movies_col_subset["duration"] < 60]

Print the first 20 rows of short_movies

print(short_movies.head(20))

Define an empty list

colors = []

Iterate over rows of netflix_movies_col_subset

for lab, row in netflix_movies_col_subset.iterrows() : if row['genre'] == "Children" : colors.append("red") elif row['genre'] == "Documentaries" : colors.append("blue") elif row['genre'] == "Stand-Up" : colors.append("green") else: colors.append("black")

Inspect the first 10 values in your list

print(colors[:11])

Set the figure style and initalize a new figure

plt.style.use('fivethirtyeight') fig = plt.figure(figsize=(12,8))

Create a scatter plot of duration versus release_year

plt.scatter(netflix_movies_col_subset["release_year"],netflix_movies_col_subset["duration"],c=colors)

Create a title and axis labels

plt.xlabel("Release Year") plt.ylabel("Duration(min)") plt.title("Movie duration by year of release")

Show the plot

plt.show()

Are we certain that movies are getting shorter?

are_movies_getting_shorter = "No, all movies are not getting shorter but we can conclude more short movies are produced lately"