How Can I Efficiently Combine Multiple CSV Files into a Single Pandas DataFrame?

Reading and Combining Multiple CSV Files into a Single DataFrame

Problem Scenario

The task is to read multiple CSV files from a directory into pandas and combine them into one DataFrame.

pandas Methodologies

Pandas offers intuitive methods for concatenating multiple dataframes:

• pd.concat(dfs, ignore_index=True): Concatenates dataframes vertically, ignoring the original index.

Implementation

To achieve the desired result, each CSV file is read into a dataframe. The concat method is then utilized to concatenate these individual dataframes into a single comprehensive DataFrame.

Code Snippet:

import glob
import pandas as pd

path = r'C:\DRO\DCL_rawdata_files'
filenames = glob.glob(path + "/*.csv")

dfs = []
for filename in filenames:
    dfs.append(pd.read_csv(filename, header=0))

big_frame = pd.concat(dfs, ignore_index=True)

print(big_frame)

Additional Notes

• Ensure that all CSV files have the same columns, as concat requires a uniform column structure.
• Consider adding a column to identify each data source for traceability purposes.
• Utilize pathlib for more advanced file handling capabilities.

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