Python Challenge: PyBank & PyPoll

Project Overview

This project includes two Python scripting tasks: PyBank and PyPoll. Both tasks utilize Python to analyze real-world datasets, one for financial analysis and the other for election vote counting.

PyBank: Financial Record Analysis

In this challenge, a Python script is created to analyze financial records from a dataset (budget_data.csv) with the following details:

• Dataset Columns: Date, Profit/Losses
• Tasks:
  • Calculate the total number of months in the dataset.
  • Compute the net total of "Profit/Losses" over the entire period.
  • Calculate the changes in "Profit/Losses" and the average of those changes.
  • Identify the greatest increase in profits (date and amount).
  • Identify the greatest decrease in profits (date and amount).

The script outputs the analysis to the terminal and saves the results to a text file.

PyPoll: Election Vote Analysis

In this challenge, we are tasked with analyzing election data from the dataset (election_data.csv) to help automate the vote-counting process. The dataset contains the following columns:

• Dataset Columns: Voter ID, County, Candidate
• Tasks:
  • Count the total number of votes cast.
  • List all candidates who received votes.
  • Calculate the percentage of votes each candidate won.
  • Calculate the total votes for each candidate.
  • Determine the winner of the election based on popular vote.

The script outputs the analysis to the terminal and saves the results to a text file.

Tools Used

• Python: Scripting language used for data analysis.
• Pandas: Library used for data manipulation and analysis.

How to Run

1. Clone this repository.
2. Install the required Python packages.
3. Run the pybank.py or pypoll.py script in a Python environment.
4. Results will be displayed in the terminal and saved as a .txt file.

Contributors

• Sakina Jaffri - Python scripting, data analysis, and report generation.