PyBank

In this project, I created a Python script for analyzing the financial records of a company using a set of financial data called budget_data.csv. The dataset is composed of two columns: Date and Profit/Losses.

The Python script 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

The final script prints the analysis to the terminal and export a text file with the results.

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Financial Analysis from Jan-2010 to Feb-2017
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Total Months: 86
Total: $38382578
Average Changes: $-2315.12
Greatest Increase in Profits: Jan-2012  ($1926159)
Greatest Decrease in Profits: Aug-2013  ($-2196167)
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PyDoll

In this project, the Python script helps a town to modernize its vote-counting process using a set of poll data called election_data.csv. The dataset is composed of three columns: Voter ID, County, and Candidate. The Python script 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.

In addition, the final script prints the analysis to the terminal and export a text file with the results.

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Election Results
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Total Votes: 3521001
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Khan: 63.0% (2218231)
Correy: 20.0% (704200)
Li: 14.0% (492940)
O'Tooley: 3.0% (105630)
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Winner: Khan
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