conditional-format.py

import pandas as pd
import matplotlib.pyplot as plt

# Step 1: Import CSV as DataFrame
def load_csv(file_path):
    return pd.read_csv(file_path)

# Step 2: Apply Conditional Formatting and Export to PDF
def apply_pdf_conditional_formatting(df, filename):
    # Create figure and axis
    fig, ax = plt.subplots(figsize=(10, len(df)*0.5))

    # Define colors based on 'RankDiff' column
    cell_colors = []
    for index, row in df.iterrows():
        if pd.notnull(row['RankDiff']):
            if row['RankDiff'] > 20:
                cell_colors.append(['#FF9999'] * len(row))
            elif row['RankDiff'] < -20:
                cell_colors.append(['#99FF99'] * len(row))
            else:
                cell_colors.append(['#FFFFFF'] * len(row))
        else:
            cell_colors.append(['#FFFFFF'] * len(row))

    # Create the table with colored cells
    table = ax.table(cellText=df.values,
                     colLabels=df.columns,
                     cellLoc='center',
                     loc='center',
                     cellColours=cell_colors)

    # Remove axis
    ax.axis('off')

    # Save figure as PDF
    plt.savefig(filename, bbox_inches='tight')

# Main function to integrate all steps
def main(csv_file_path, pdf_output_path):
    # Load CSV
    df = load_csv(csv_file_path)

    # Apply conditional formatting and save to PDF
    apply_pdf_conditional_formatting(df, pdf_output_path)

# Replace with your file paths
csv_file_path = 'draftsheet.csv'
pdf_output_path = 'draftsheet.pdf'

# Run the main function
main(csv_file_path, pdf_output_path)