Python implements matching the database based on the content of a column in Excel table

The following is a sample code based on Python, using the pandas library and the Brightway2 library to match the database according to the content of a column of the Excel table, and then grab the matching successful data and export it as a new Excel table. Here, assume that you have successfully imported the database and understand the structure of the data in the database.

Install the necessary libraries

First make sure you have the pandas and Brightway2 libraries installed. If not installed, you can use the following command to install:

pip install pandas brightway2

Sample code

import pandas as pd
import bw2data as bd

def match_and_export(excel_file_path, db_name, match_column_name, match_condition):
    # Read Excel file    df = pd.read_excel(excel_file_path)
    # Get data of matching columns    match_values = df[match_column_name].tolist()

    # Load the Brightway2 database    .set_current('your_project_name')  # Set the current project name, which needs to be replaced with the actual project name    db = (db_name)

    # Used to store data that matches successfully    matched_data = []

    # traverse matching values ​​in Excel    for value in match_values:
        # Match according to matching conditions        for activity in db:
            if match_condition(activity, value):
                # Here you can grab more information as needed                data = {
                    'excel_value': value,
                    'activity_name': activity['name'],
                    'activity_code': activity['code']
                }
                matched_data.append(data)

    # Convert the matching successful data to DataFrame    result_df = (matched_data)

    # Export as a new Excel file    result_df.to_excel('matched_data.xlsx', index=False)
    print("Matched data exported to matched_data.xlsx")

# Example matching conditional functiondef example_match_condition(activity, value):
    # Here it is assumed that the matching is based on the activity name, and you can modify it according to the actual needs.    return activity['name'] == value

# Sample callif __name__ == "__main__":
    excel_file_path = 'your_excel_file.xlsx'  # Replace with the actual Excel file path    db_name = 'your_database_name'  # Replace with the actual database name    match_column_name = 'your_column_name'  # Replace with the actual matching column name
    match_and_export(excel_file_path, db_name, match_column_name, example_match_condition)

Code description

Read Excel file: Use the pandas library's read_excel function to read the Excel file and get the data of the specified column.

Loading the database: Use the function of the Brightway2 library to load the specified database.

Match data: Iterate over the matching values ​​in Excel and find matching activities in the database according to the matching conditions.

Crawl data: For successful matching activities, store relevant information in a list.

Export data: Convert the matching successful data into a DataFrame object of pandas and export it as a new Excel file using the to_excel function.

Things to note

Please replace 'your_project_name', 'your_excel_file.xlsx', 'your_database_name', and 'your_column_name' with the actual project name, Excel file path, database name, and matching column name.

The example_match_condition function is an example matching condition that you can modify according to actual needs.

If you are using an ecoinvent database, you need to make sure that the database has been imported and configured correctly. When using Brightway2, some additional configuration and initialization may be required.

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