How to Combine DataFrames Generated in a For Loop into a Single DataFrame?

Appending DataFrames Generated in a For Loop

When working with numerous Excel files that need to be combined into a single DataFrame, you may encounter the challenge of appending the dataframes during iteration. This question addresses this issue, where a user attempted to append dataframes within a for loop but faced difficulties.

The provided solution utilizes the pd.concat function to effectively merge a list of dataframes into a single DataFrame. The code snippet below demonstrates this approach:

<code class="python">appended_data = []
for infile in glob.glob("*.xlsx"):
    data = pandas.read_excel(infile)
    # Store DataFrame in a list
    appended_data.append(data)
# See pd.concat documentation for more info
appended_data = pd.concat(appended_data)
# Write DataFrame to an excel sheet
appended_data.to_excel('appended.xlsx')</code>

By iteratively reading excel files and appending their dataframes to a list, pd.concat is then used to combine all dataframes into a single entity. This final dataframe can be saved as a new Excel file using the to_excel function.

This approach allows for the accumulation of data from multiple files into a single DataFrame, providing a comprehensive view of the combined data for further analysis or processing.

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