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| import pandas as pd | |
| # Read in endorsements | |
| pp = pd.read_csv("pp_endorsements.csv") | |
| rff = pd.read_csv("rff_endorsements.csv") | |
| now = pd.read_csv("now_endorsements.csv") | |
| # Merge by name | |
| df = pd.merge(pp[["Candidate", "Endorsed by"]], rff[["Candidate", "Endorsed by"]], on = "Candidate", how = "outer") | |
| df = pd.merge(df, now[["Candidate", "Endorsed by"]], on = "Candidate", how = "outer") | |
| # Fill NaN values with an empty string for concatenation | |
| df.fillna('', inplace = True) | |
| # Concatenate the endorsements into a single string | |
| df['Endorsed by'] = df['Endorsed by_x'] + ', ' + df['Endorsed by_y'] + ', ' + df['Endorsed by'] | |
| df['Endorsed by'] = df['Endorsed by'].str.strip(', ') | |
| df.drop(columns=["Endorsed by_x", "Endorsed by_y"], inplace = True) | |
| # Write to CSV | |
| df.to_csv("reproductive_endorsements.csv", index = False) |