• Background
• PyBank
  • Instructions
  • Results
• PyPoll
  • Instructions
  • Results

There are two challenges here that give me a taste of what's to come with Python. Both of these challenges encompasses a real-world situtation where my newfound Python knowledge will come in handy. It is something that Excel will not be good at!

In this challenge, I am tased to create a Python script for analyzig the financial records of my company. I am given a set of financial data with two columns: Date and Profit/Losses.

For the assignment I created a Python script that analyzes the records to calculate each of the following:

• Total number of months included in the dataset

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

• The average of the changes in "Profit" and "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.

Here are the results that I found:

Financial Analysis
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Total Months: 86
Total Revenue: $38,382,578.00
Average Revenue Change: $-2,315.12
Greatest Increase in Profits: Feb-2012 $1,926,159.00
Greatest Decrease in Profits: Sep-2013 $-2,196,167.00

In this challenge, I am tasked with helping a small, rural town modernize its vote-counting process.

I will be given a set of poll data with three columns: Voter Id, County and Candidate. My task is to 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 the popular vote.

Here are the results that I found:

Election Results
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Total Votes: 3,521,001
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Khan: 63.000% (2,218,231)
Correy: 20.000% (704,200)
Li: 14.000% (492,940)
O'Tooley: 3.000% (105,630)
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Winner:  Khan
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