Skip to content

This project utilizes Python for data preprocessing and analysis, along with Power BI for creating an interactive dashboard, to analyze trends and insights within the movie industry. The project encompasses data collection, cleaning, exploration, visualization, and interpretation to provide valuable insights into various aspects of the industry.

Notifications You must be signed in to change notification settings

hrishabht5/Top-Movies-analysis-

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Movies Analysis Project This project utilizes Python for data preprocessing and analysis, along with Power BI for creating an interactive dashboard, to analyze trends and insights within the movie industry. The project encompasses data collection, cleaning, exploration, visualization, and interpretation to provide valuable insights into various aspects of the movie industry.

Key Features:

Data Collection: Utilizes public datasets or APIs to gather information about movies, including attributes such as title, genre, release year, ratings, and box office revenue.

Data Preprocessing: Applies data cleaning techniques using Python to handle missing values, outliers, and inconsistencies, ensuring the data is accurate and ready for analysis.

Exploratory Data Analysis (EDA): Conducts exploratory data analysis to uncover patterns, trends, and relationships within the movie dataset. This includes visualizations such as histograms, scatter plots, and heatmaps to understand the distribution and correlation of different variables.

Statistical Analysis: Performs statistical analysis to identify significant insights, such as the average ratings of different genres, the relationship between budget and revenue, or the distribution of movie ratings over time.

Dashboard Creation: Develops an interactive dashboard using Power BI to visualize the analysis results. The dashboard includes dynamic visualizations, filters, and slicers to enable users to explore and interact with the data.

Insight Generation: Presents key findings and insights derived from the analysis, such as popular movie genres, seasonal trends in box office revenue, or the impact of critical ratings on movie success.

How to Use:

Data Collection and Preprocessing: Obtain the movie dataset and preprocess it using Python scripts provided in the project repository.

Exploratory Data Analysis: Run Python scripts to perform exploratory data analysis and generate insights into the movie dataset.

Dashboard Visualization: Open the Power BI dashboard file included in the repository to explore interactive visualizations and dive deeper into the analysis results.

Interactivity: Utilize filters, slicers, and drill-down capabilities within the Power BI dashboard to interactively explore different aspects of the movie data.

Contribution:

Contributions to this project are welcome! If you have suggestions for enhancements, additional analysis techniques, or bug fixes, please feel free to submit a pull request.

About

This project utilizes Python for data preprocessing and analysis, along with Power BI for creating an interactive dashboard, to analyze trends and insights within the movie industry. The project encompasses data collection, cleaning, exploration, visualization, and interpretation to provide valuable insights into various aspects of the industry.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published