Investigating_Netflix_Movies

Netflix Movie Exploration with Pandas and Matplotlib

This repository explores movie data from Netflix, focusing on movie duration, genre distribution, and trends across release years.

Data Source:

The data for this analysis is expected to be in a CSV file named "netflix_data.csv". This file should contain attributes like title, type (movie/show), genre, release year, and duration.

Code Structure:

The provided Python script ([Investigating_Netflix_Movies]) utilizes pandas for data manipulation and visualization, and matplotlib for creating charts. The script is organized into three sections:

1. Data Preparation:

   • Imports pandas and matplotlib libraries.
   • Reads the "netflix_data.csv" file into a pandas DataFrame.
   • Filters the data for movies only and selects relevant columns (title, country, genre, release year, duration).
   • Creates a subset of movies with duration less than 60 minutes (optional analysis).
   • Defines a list of important genres for further exploration ("Children", "Documentaries", "Stand-Up").

2. Visualization 1: Movie Duration vs. Release Year

   • Creates a scatter plot with release year on the x-axis and duration on the y-axis.
   • Assigns colors to data points based on their genre for visual distinction.

3. Visualization 2 & 3: Genre Analysis based on Release Year

   • Filters movies for the pre-defined list of important genres.
   • Visualization 2.1: Calculates the average movie duration for each genre across release years using pivot tables.
     • Creates a line plot showing the average duration trend for each genre.
   • Visualization 2.2: Creates a pivot table to count the number of movies for each genre in each release year.
     • Generates a line plot with release year on the x-axis and separate lines for each genre, representing the movie count for that genre in each year.

Running the Script:

1. Ensure you have pandas and matplotlib libraries installed (pip install pandas matplotlib).
2. Place the script ([script_name.py]) and the data file ("netflix_data.csv") in the same directory.
3. Run the script from your terminal using python [Investigating_Netflix_Movies].

Expected Output:

The script will generate three visualizations:

1. A scatter plot depicting movie duration distribution across release years, colored by genre. Looking at the scatter plot, we can observe a few trends:

   Genre and Release Year: Stand-up comedies (yellow) seem to be concentrated in more recent release years (farther right on the x-axis), whereas children's movies (red) show a wider spread across years. This might suggest a rise in stand-up comedy content on Netflix in recent times.

   Genre and Duration: There seems to be a wider spread of durations for documentaries (blue) compared to children's movies (red) and stand-up comedies (yellow). Documentaries might encompass a larger variety of short and long formats, while children's movies and stand-up comedies tend to have shorter durations on average.

2. A line plot showing the average movie duration trend for each genre over release years. The data suggests some interesting trends:

   Children's Content: There might be an increase in the duration of children's content around 1990. It's worth investigating if this coincides with a specific shift in children's programming or media formats.

   Documentaries: The graph reveals how documentary lengths have changed over time.Before 1990's the duration was very great after it started fluctuating towards shorter duration

3. A line plot showcasing the number of movies released for each genre across different release years.

   This graph shows the number of titles on Netflix by genre and release year. The data suggests that the number of titles in all genres has increased over time. Documentaries appears to be the most explosive genre on Netflix, with the number of titles in this genre increasing significantly in recent years. The number of Children's Movies on Netflix has also grown steadily over time. Stand-Up comedy are the least common on Netflix, but the number of titles in this genre has also increased in recent years.

Further Exploration:

This code provides a basic framework for exploring movie data on Netflix. You can modify the script to:

• Analyze additional genres.
• Explore relationships between movie duration, genre, and other attributes.
• Create different visualizations based on your interests.

Feel free to adapt and extend this code for further analysis of the Netflix movie data!