In this challenge, you are tasked with creating a Python script for analyzing the financial records of your company. You will be given two sets of revenue data (budget_data_1.csv and budget_data_2.csv). Each dataset is composed of two columns: Date and Revenue. (Thankfully, your company has rather lax standards for accounting so the records are simple.)
Your task is to create a Python script that analyzes the records to calculate each of the following:
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The total number of months included in the dataset
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The total amount of revenue gained over the entire period
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The average change in revenue between months over the entire period
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The greatest increase in revenue (date and amount) over the entire period
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The greatest decrease in revenue (date and amount) over the entire period
As an example, your analysis should look similar to the one below:
Financial Analysis
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Total Months: 25
Total Revenue: $1241412
Average Revenue Change: $216825
Greatest Increase in Revenue: Sep-16 ($815531)
Greatest Decrease in Revenue: Aug-12 ($-652794)
Your final script must be able to handle any such similarly structured dataset in the future (your boss is going to give you more of these -- so your script has to work for the ones to come). In addition, your final script should both print the analysis to the terminal and export a text file with the results.
In this challenge, you are tasked with helping a small, rural town modernize its vote-counting process. (Up until now, Uncle Cleetus had been trustfully tallying them one-by-one, but unfortunately, his concentration isn't what it used to be.)
You will be given two sets of poll data (election_data_1.csv and election_data_2.csv). Each dataset is composed of three columns: Voter ID, County, and Candidate. Your task is to create a Python script that analyzes the votes and calculates each of the following:
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The total number of votes cast
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A complete list of candidates who received votes
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The percentage of votes each candidate won
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The total number of votes each candidate won
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The winner of the election based on popular vote.
As an example, your analysis should look similar to the one below:
Election Results
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Total Votes: 620100
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Rogers: 36.0% (223236)
Gomez: 54.0% (334854)
Brentwood: 4.0% (24804)
Higgins: 6.0% (37206)
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Winner: Gomez
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Your final script must be able to handle any such similarly-structured dataset in the future (i.e you have zero intentions of living in this hillbilly town -- so your script needs to work without massive re-writes). In addition, your final script should both print the analysis to the terminal and export a text file with the results.