Python Challenge: PyBank and PyPoll

Overview

This repository contains two Python scripts created for the Python challenge: PyBank and PyPoll. These scripts use Python to analyze large datasets, showcasing how programming can replace Excel for more efficient data processing.

Repository Structure

• PyBank/ - Contains the Python script and analysis for the PyBank financial records challenge.

  • main.py - The Python script that performs the analysis.
  • Resources/ - Folder containing the dataset used for analysis.
  • analysis/ - Folder containing the output text file with the analysis results.

• PyPoll/ - Contains the Python script and analysis for the PyPoll election results challenge.

  • main.py - The Python script that performs the analysis.
  • Resources/ - Folder containing the dataset used for analysis.
  • analysis/ - Folder containing the output text file with the analysis results.

PyBank Challenge

Objective:

Analyze the financial records in the dataset budget_data.csv to calculate:

• Total number of months.
• Total profit/loss.
• Average change in profit/loss between months.
• The greatest increase in profits.
• The greatest decrease in profits.

Script Details:

• The script reads data from the Resources/budget_data.csv file.
• It calculates the total number of months, total profit/loss, and the average change in profits.
• The greatest increase and decrease in profits are also identified.
• The results are both printed to the terminal and exported to analysis/PyBank Analysis.txt.

Example Output:

Financial Analysis
------------------------------
Total Months: 86
Total: $22564198
Average Change: $-8311.11
Greatest Increase in Profits: Aug-16 ($1862002)
Greatest Decrease in Profits: Feb-14 ($-1825558)

PyPoll Challenge

Objective:

Analyze election data in the dataset election_data.csv to determine:

• The total number of votes.
• The percentage and number of votes each candidate received.
• The winner of the election based on popular vote.

Script Details:

• The script reads data from the Resources/election_data.csv file.
• It calculates the total votes cast, each candidate's vote count, and percentage of votes.
• The winner is determined based on the highest number of votes.
• The results are both printed to the terminal and exported to analysis/PyPoll Analysis.txt.

Example Output:

Election Results
--------------------------
Total Votes: 369711
--------------------------
Charles Casper Stockham: 23.05% (85213)
Diana DeGette: 73.81% (272892)
Raymon Anthony Doane: 3.14% (11606)
--------------------------
Winner: Diana DeGette

Usage

1. Clone the repository:

   git clone https://github.com/the-eva-a/python-challenge.git
   

2. Navigate to either PyBank or PyPoll folders and run the script:

   python main.py
   

Acknowledgements

This project is part of the curriculum in the edX Data Analytics Bootcamp. Special thanks to my instructors and peers for their support and guidance.