Analyzing Bank and Election Data

This analysis is comprised of two smaller analyses, which include a dive into simple bank data and election data.

Features & Libraries

• Python

My Process:

In the first part of the project, I will write a Python script to analyze the financial records of a company. I will calculate the following information:

• Total number of months included in the dataset
• Net total amount of "Profit/Losses" over the entire period
• 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

In the second part of the project, I will write a Python script to analyze the election data from a small, rural town. I will calculate the following information:

• 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.

Example Outputs

Bank Data:

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

Election Data:

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