Movie Data Analysis

Author

Keith Galli

Overview

Code 
import pandas as pd
import matplotlib.pyplot as plt
from helpers import plot_release_year_distribution, create_keyword_wordcloud, create_genre_distribution

df = pd.read_csv("./data/TMDB-Small.csv")

#df

#df.head()

Distribution by year

Code 
plot_release_year_distribution(df)

Movie Release Year Distribution

Plotly Scatter Plot

Code 
import plotly.express as px

df['primary_genre'] = df['genres'].str.split(',').str[0].str.strip()

fig = px.scatter(df, x='vote_count', y='vote_average', hover_data=['title'], color='primary_genre', title='Vote Count vs Vote Average')
fig.show()

Word Cloud

Code 
create_keyword_wordcloud(df)

Genre Distribution

Code 
create_genre_distribution(df)

Random Movie

Code 
# Random Movie
movie = df.sample(1)

url = f"https://image.tmdb.org/t/p/w600_and_h900_bestv2{movie['poster_path'].values[0]}"

Title: Spy Kids

Description: Carmen and Juni think their parents are boring. Little do they know that in their day, Gregorio and Ingrid Cortez were the top secret agents from their respective countries. They gave up that life to raise their children. Now, the disappearances of several of their old colleagues forces the Cortez\\’ return from retirement. What they didn\\’t count on was Carmen and Juni joining the “family business.”