This Python script, avg_trans_amt.py, leverages the Pandas library to analyze transaction data and calculate the average transaction amount on a monthly basis. The code reads input from an Excel file, processes the data, and outputs a dictionary containing the average transaction amount for each month.
Key Features:
Efficiently handles transaction data with Pandas DataFrames. Organizes transaction amounts on a monthly basis for easy trend analysis. Outputs a dictionary with monthly average transaction amounts. Usage:
Input your transaction data in the provided Excel file (avg_trans_amt.xlsx). Run the script to obtain a dictionary with monthly average transaction amounts.
Sample Output: {'2024-01': 125.0, '2024-02': 225.0, '2024-03': 325.0}
Note: Ensure that the Pandas library is installed in your Python environment (pip install pandas).
Motivation: This project serves as a practical example of data analysis and manipulation, showcasing skills relevant to data science roles. The script can be adapted for various datasets and provides a foundation for further exploration and visualization.
Feel free to explore and adapt this code for your specific data analysis needs.