/Py-Me-Up-Charlie

Python-based Analysis of a Company's Financial Records and Votes in a Small, Rural Town

Primary LanguagePython

Py Me Up, Charlie - Python Analysis of Financial Records and Vote Counting

PyBank

Created a Python script for analyzing the financial records of a company from a CSV file containing Date and Profit/Losses columns.

  • The Python script calculated each of the following:

    • The total number of months included in the dataset

    • The net total amount of "Profit/Losses" over the entire period

    • The average of the changes in "Profit/Losses" over the entire period

    • The greatest increase in profits (date and amount) over the entire period

    • The greatest decrease in losses (date and amount) over the entire period

  • Formatted the output analysis to appear as:

    Financial Analysis
--------------------------------------------------
Total Months: 86
Net Total Amount: $38382578
Average  Change: $-2315.12
Greatest Increase in Profits: Feb-2012 ($1926159)
Greatest Decrease in Profits: Sep-2013 ($-2196167)

PyPoll

Helped a small, rural town modernize its vote-counting process using a CSV set of poll data composed of Voter ID, County, and Candidate columns.

  • Created a Python script that analyzes the votes and calculates each of the following:

    • The total number of votes cast

    • A complete list of candidates who received votes

    • The percentage of votes each candidate won

    • The total number of votes each candidate won

    • The winner of the election based on popular vote.

  • Formatted the output analysis to appear as:

    Election Results
-------------------------
Total Votes: 3521001
-------------------------
Khan: 63.000% (2218231)
Correy: 20.000% (704200)
Li: 14.000% (492940)
O'Tooley: 3.000% (105630)
-------------------------
Winner: Khan
-------------------------

Data Sources

Technologies Used

  • Python

Author

Kiran Rangaraj - LinkedIn: @Kiran Rangaraj