How to Import Custom Python Functions and Merge Excel Files Like a Pro

In many real‑world projects developers repeatedly copy‑paste the same code. Instead of rewriting functions each time, you can package them into a Python module and import them just like built‑in libraries.

Background

Often you need to combine all .xlsx files in a directory into a single workbook. The following function merges the files, keeps the original data format, and saves the result as data_ok.xlsx inside a filtered_data folder.

def concat_excels(pattern):
    import pandas as pd
    import os
    import glob

    if not os.path.exists('filtered_data'):
        os.mkdir('filtered_data')

    file_paths = glob.glob(pattern)
    df = pd.DataFrame()
    for file_path in file_paths:
        df_ = pd.read_excel(file_path)
        df = pd.concat([df, df_])

    df.to_excel('filtered_data/data_ok.xlsx', index=False)
    print('Finished!')

if __name__ == '__main__':
    concat_excels('*.xlsx')

Specific Steps

1. Locate the installation directory of the third‑party library you are using (e.g., requests) by running import requests, print(requests.__file__) in your editor; the highlighted path shows where to place your custom module.

2. Save the function in a .py file, give it a short name, and move the file into the highlighted directory.

3. In the folder containing the Excel files, create a new Python script (e.g., merge_data.py).

4. Write the import statement and call the function to perform the merge. The screenshot below shows the script running successfully. from 模块名 import * means import all functions from the module, allowing direct calls.

Extension

By storing frequently used utilities in your own module, you can reuse them across projects with a single import. For example, you can wrap image loading, color correction, and display logic into functions and call them with one line of code.

Demo screenshots illustrate the streamlined workflow.