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In this challenge, I created a Python script for analyzing the financial records of the company. The data analysed is budget_data.csv.
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Created a Python script that analyzed 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 net total amount of "Profit/Losses" over the entire period
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The average of the changes in "Profit/Losses" over the entire period
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The greatest increase in profits (date and amount) over the entire period
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The greatest decrease in losses (date and amount) over the entire period
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As an example, our analysis 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)
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In this challenge, I'm tasked with helping a small, rural town modernize its vote counting process.
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The data analysed is election_data.csv(PyPoll/Resources/election_data.csv). The dataset is composed of three columns:
Voter ID
,County
, andCandidate
. We created a Python script that analyzes the votes and calculates each of the following:-
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.
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As an example, our analysis 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 -------------------------
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In addition, the final script print the analysis to the terminal and export a text file with the results.