Python Homework - Py Me Up, Charlie

Background

Well... you've made it! It's time to put away the Excel sheet and join the big leagues. Welcome to the world of programming with Python. In this homework assignment, you'll be using the concepts you've learned to complete the two Python Challenges, PyBank and PyPoll. Both of these challenges encompasses a real-world situation where your newfound Python scripting skills can come in handy. These challenges are far from easy so expect some hard work ahead!

PyBank

In this challenge, you are tasked with creating a Python script for analyzing the financial records of your company. You will give a set of financial data called budget_data.csv. The dataset is composed of two columns: Date and Profit/Losses. (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:

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

As an example, your analysis should look similar to the one below: 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)

In addition, your final script should both print the analysis to the terminal and export a text file with the results.

PyPoll

In this challenge, you are tasked with helping a small, rural town modernize its vote counting process.

You will be give a set of poll data called election_data.csv. The 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:

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.

As an example, your analysis should look similar to the one below: Election Results

Total Votes: 3521001

Khan: 63.000% (2218231) Correy: 20.000% (704200) Li: 14.000% (492940) O'Tooley: 3.000% (105630)

Winner: Khan

Tech Environment Used:

Python, VSCode, GitHub.

DSB011/Python-Py-Me-Up

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