This project aims to analyze a user's screen time using Python, focusing on which applications and websites they use and for how long. The project utilizes various libraries such as pandas, numpy, plotly.express, and plotly.graph_objects to process, visualize, and analyze the data.

To run the project, you would typically follow these steps:

1. Clone the repository : If the project is hosted on a version control system like GitHub, you would first clone the repository to your local machine.

git clone https://github.com/username/project-name.git

Replace https://github.com/username/project-name.git with the actual URL of the repository.

2. Navigate to the project directory : Use the cd command to navigate to the project directory.

cd project-name

3. Install dependencies : Most JavaScript projects use npm (Node Package Manager) to manage dependencies. Run the following command to install the project's dependencies:

npm install

4. Enter the below one:

python3 main.py

If the project is not hosted on a version control system, you would need to obtain the project files through other means, such as downloading a ZIP file and extracting it. The rest of the steps would remain the same.

The data used in this project is stored in a CSV file named "Screentime-App-Details.csv". The dataset contains information about the user's screen time, including the date, app, usage, notifications, and the number of times the app was opened.

The data is preprocessed using pandas to check for missing values and to generate descriptive statistics.

The project includes several visualizations to help analyze the data:

1. Usage of Apps by User (Bar Chart) : This chart shows the usage of different apps by the user on different dates.
2. Notifications of Apps to the User (Bar Chart) : This chart shows the number of notifications received from different apps on different dates.
3. Number of times Apps opened by the User (Bar Chart) : This chart shows the number of times different apps were opened by the user on different dates.
4. Relationship between the number of notifications and the amount of usage (Scatter Plot) : This plot shows the relationship between the number of notifications and the amount of usage. The size of the points represents the number of notifications, and a trendline is added to show the linear relationship between the two variables.

The project provides a summary of the analysis, which states that there is a linear relationship between the number of notifications and the amount of usage. This means that more notifications result in more use of smartphones.

To run the project, simply execute the Python script. The visualizations will be displayed in the browser.

The project requires the following libraries:

• pandas
• numpy
• plotly.express
• plotly.graph_objects

These libraries can be installed using pip:

pip3 install pandas numpy plotly

This project is licensed under the MIT License.