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# Assuming you have loaded both Excel files into pandas DataFrames
# Replace 'entity_file_path' and 'participation_file_path' with your actual file paths
entity_file_path = 'path_to_entity_file.xlsx'
participation_file_path = 'path_to_participation_file.xlsx'
# Load the Entity Hierarchy and Participation files
entity_df = pd.read_excel(entity_file_path)
participation_df = pd.read_excel(participation_file_path)
# Merge the Entity Hierarchy information into the Participation file based on Group_Name
merged_df = pd.merge(participation_df, entity_df, on='Group_Name', how='left', suffixes=('_participation', '_entity'))
# Identify missing values in the columns from Entity Hierarchy
missing_values = merged_df[merged_df['Group_Level_entity'].isnull()]
# Iterate over the missing values and fill them using Parent_Name
for index, row in missing_values.iterrows():
parent_name = row['Parent_Name_participation']
parent_level = row['Parent_Level_participation']
# Filter the Entity Hierarchy based on Parent_Name and Parent_Level
matching_entity = entity_df[(entity_df['Group_Name'] == parent_name) & (entity_df['Group_Level'] == parent_level)]
# Sum the values for Recipients and Respondents for the matching Group_Names
sum_recipients = matching_entity['Recipients'].sum()
sum_respondents = matching_entity['Respondents'].sum()
# Calculate the Score
score = sum_respondents / sum_recipients if sum_recipients > 0 else 0
# Update the missing values in the Participation file
participation_df.loc[index, 'Group_Name'] = parent_name
participation_df.loc[index, 'Group_Level'] = parent_level
participation_df.loc[index, 'Recipients'] = sum_recipients
participation_df.loc[index, 'Respondents'] = sum_respondents
participation_df.loc[index, 'Score'] = score
# Save the updated Participation file
participation_df.to_excel('updated_participation_file.xlsx', index=False)
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