Overview

This project provides a Python script for analyzing and visualizing ERP (Event-Related Potential) data combined with demographic information. The script processes, cleans, and visualizes the data using pandas for data manipulation and matplotlib for plotting.
File Contents

    Implementation Code (Implementation code.py): The main script for data processing and visualization.
    Data Files (not included in the repository):
        demographic.csv: Contains demographic information of subjects. Ensure to remove spaces from column names.
        ERPdata.csv: Contains ERP data for subjects.

Prerequisites

Make sure you have the following Python libraries installed:

    pandas
    matplotlib
    numpy


How to Use

    Load the Data: The script loads two CSV files: demographic.csv and ERPdata.csv. Ensure that these files are placed in the data/ directory relative to the script.

    Data Preprocessing:
        Columns in demographic.csv have spaces at the beginning, which are removed.
        The ERP data is merged with demographic information based on the subject column.
        Group labels in the data are converted to meaningful strings ('Control' and 'Schizo').
        Baseline correction is performed by filtering the time window to between -100 ms and 300 ms and performing necessary calculations.

    ERP Data Manipulation:
        The script modifies the data for specific conditions and electrodes (Fz, FCz, Cz).
        Reshaping of data using pd.melt() is performed to make it suitable for visualization.

    Visualization:
        The data is visualized using matplotlib. Ensure that the %matplotlib notebook magic command is set for interactive plotting if you are running the script in a Jupyter Notebook.