PyBank and PyPoll

• PyBank: Analysis on monthly Profit/Loss data
• PyPoll: Analysis on election result

Background

In this work, I created python scripts for analyzing the financial records of PyBank and the election result of PyPoll.

PyBank

• In this work, I created a Python script for analyzing the financial records of PyBank. With a set of financial data called budget_data.csv, the dataset is composed of two columns: Date and Profit/Losses.

• Create a Python script that analyzes the records to calculate 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

  Financial_Analysis

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

PyPoll

• In this work, I created a Python script for analyzing the votes of election result of PyPoll.

• With a set of poll data called election_data.csv, the dataset is composed of three columns: Voter ID, County, and Candidate.

• Create 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.

Election_Results

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

Funke Olaleye | Data Analytics and Visualization