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What is the voter turnout percentage by precinct?

Let's start by loading the data from the file Sheet1-Table 1.csv to analyze the voter turnout percentage by precinct.

So each row that starts with PCT means the next three rows refer to information about the precinct, can you separate each precinct and print out the total voter turnout by precinct?

To calculate the total voter turnout by precinct, we'll first separate each precinct based on the rows that start with 'PCT'. Then, we'll sum up the voter turnout for each precinct. Let's proceed with this analysis.
Here's the total voter turnout by precinct. Each precinct is listed with its corresponding number of voters who cast their votes.

This is great, can you now actually show me a graph of the turnout percentage for each of these precincts? Look at the row "Total" for each precinct

To visualize the turnout percentage for each precinct, we'll extract the 'Total' row for each precinct to calculate the percentage. Then, we'll create a graph to display these percentages. Let's start by extracting the necessary data.
Now, let's create a bar graph to visualize the turnout percentage for each precinct.

Only issue is the name of the precinct is not always total, the name of the precinct actually shows up 3 rows before the one that is named total, can you replot it with that information?

Given the new information that the precinct name appears 3 rows before the 'Total' row, we'll adjust our approach to correctly identify the precinct names and their corresponding turnout percentages. Let's replot the graph with this updated information.

Can you add a line to the chart that shows the average for voter turnout across all districts?

Can you breakdown the total number of voters by mail and in person in a pie chart?

Let's load the new data from Sheet1-Table 1.csv to break down the total number of voters by mail and in person. We'll then create a pie chart to visualize this breakdown.
To create a pie chart that breaks down the total number of voters by mail and in person, we'll first need to extract the relevant data from our dataset.

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