How Can I Use Pandas to Append Data to an Existing CSV File?

Extending CSV Files with Pandas

When working with large datasets, it can be necessary to add data to an existing CSV file. Pandas, a powerful data manipulation library in Python, provides the to_csv() function for exporting data to CSV formato. This article explores the use of to_csv() to append data to an existing CSV file, ensuring compatibility with its structure.

Appending to Existing CSV Files

The to_csv() function offers a write mode parameter, allowing users to specify how the data is written to the file. By setting this parameter to 'a', the data is appended to the existing file. For example:

df.to_csv('my_csv.csv', mode='a', header=False)

Here, the dataframe df is appended to the CSV file named 'my_csv.csv'. The header=False parameter ensures that the header row is not written multiple times.

It's important to note that the default write mode for to_csv() is 'w', which overwrites the existing file. To ensure append mode, explicitly specify 'a'.

Handling Initial File Absence

If the target CSV file doesn't exist initially, the header row may not be written correctly if using append mode. To address this, you can use the following variation:

import os
output_path='my_csv.csv'
df.to_csv(output_path, mode='a', header=not os.path.exists(output_path))

This code checks if the file exists using os.path.exists(). If it doesn't, it writes the header row by setting header=True. Otherwise, it appends the data without the header.

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