Turnout Tier Categorization

This Python script contains a function add_turnout_tier that adds a new categorical column called turnout_tier to a pandas DataFrame. The categorization is based on the values in a specified numeric column.

Function Description

add_turnout_tier

Adds a new categorical column turnout_tier to the DataFrame based on the specified numeric column.

Parameters:

• df (pandas.DataFrame): The DataFrame containing the numeric column.
• numeric_column (str): The name of the numeric column to base the turnout_tier on.

Returns:

• pandas.DataFrame: The DataFrame with the new turnout_tier column added.

Turnout Tier Criteria:

• > 80: "Very likely to vote regardless of campaign"
• 70-79: "Turnout Tier 1"
• 50-69: "Turnout Tier 2"
• 30-59: "Turnout Tier 3"
• < 30: "Very unlikely to vote regardless of campaign"

Usage

Example

import pandas as pd

# Define the function
def add_turnout_tier(df, numeric_column):
    def categorize_turnout(value):
        if value > 80:
            return "Very likely to vote regardless of campaign"
        elif 70 <= value <= 79:
            return "Turnout Tier 1"
        elif 50 <= value <= 69:
            return "Turnout Tier 2"
        elif 30 <= value <= 59:
            return "Turnout Tier 3"
        else:
            return "Very unlikely to vote regardless of campaign"

    df['turnout_tier'] = df[numeric_column].apply(categorize_turnout)
    return df

# Example usage
data = {
    'voter_score': [85, 75, 60, 45, 25]
}
df = pd.DataFrame(data)
df = add_turnout_tier(df, 'voter_score')
print(df)