Investigating Netflix Movies and Guest Stars in The Office

# Create the years and durations lists
years = [x+1 for x in range(2010,2020)]
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)

# 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'])

# Create a title
plt.xlabel("release_years")
plt.ylabel("durations")

# 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
netflix_df.head()

# Subset the DataFrame for type "Movie"
netflix_df_movies_only=netflix_df[netflix_df.type=='Movie']
netflix_df_movies_only.head()
# Select only the columns of interest
netflix_movies_col_subset = netflix_df_movies_only.loc[:,['title','country','genre','release_year','duration']]

# Print the first five rows of the new DataFrame
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'])

# Create a title
plt.title("Netflix durations vs years")

# 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.iloc[: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[:10])

# 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'],color=colors)

# Create a title and axis labels
plt.xlabel('Release year')
plt.ylabel('Release year')
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 = "we are not sure"