Python pandas to_csv zip format

Python pandas to_csv zip format

You can use the to_csv function in Pandas along with the zipfile module to save a DataFrame in CSV format and then compress it into a zip file. Here's how you can do it:

import pandas as pd import zipfile # Create a sample DataFrame data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 22]} df = pd.DataFrame(data) # Save the DataFrame to a CSV file csv_filename = 'data.csv' df.to_csv(csv_filename, index=False) # Compress the CSV file into a zip archive zip_filename = 'data.zip' with zipfile.ZipFile(zip_filename, 'w', zipfile.ZIP_DEFLATED) as zipf: zipf.write(csv_filename, arcname='data.csv')

In this example:

  1. A sample DataFrame is created.
  2. The DataFrame is saved to a CSV file using df.to_csv().
  3. The CSV file is then compressed into a zip archive using the zipfile.ZipFile context manager. The 'w' parameter indicates that you're writing to the zip archive, and zipfile.ZIP_DEFLATED specifies the compression method.

After running this code, you'll have a zip file named data.zip containing the CSV file data.csv.

Examples

  1. How to save a Pandas DataFrame to a compressed ZIP file?

    • Use to_csv() with a ZipFile object to save the CSV file in ZIP format.
    import pandas as pd import zipfile df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Create a ZIP file and write the CSV inside it with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('data.csv', 'w') as f: df.to_csv(f, index=False)

  2. How to save a CSV file inside a ZIP archive with a custom compression level?

    • Define a specific compression level when creating the ZIP file.
    df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Use a custom compression level when creating the ZIP file with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_BZIP2) as zf: with zf.open('data.csv', 'w') as f: df.to_csv(f, index=False)

  3. How to save multiple CSV files into a single ZIP archive using Pandas?

    • Add multiple DataFrames into separate CSV files within a single ZIP file.
    df1 = pd.DataFrame({ 'Name': ['Alice', 'Bob'], 'Age': [25, 30], }) df2 = pd.DataFrame({ 'Name': ['Charlie', 'David'], 'Age': [35, 40], }) # Add multiple CSV files into a single ZIP archive with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('df1.csv', 'w') as f: df1.to_csv(f, index=False) with zf.open('df2.csv', 'w') as f: df2.to_csv(f, index=False)

  4. How to read a CSV file from a ZIP archive in Pandas?

    • Open the ZIP file and use read_csv() to read the CSV content.
    import io # Read CSV from ZIP archive with zipfile.ZipFile('data.zip', 'r') as zf: with zf.open('data.csv') as f: df = pd.read_csv(io.TextIOWrapper(f)) print(df) # Output: # Name Age # 0 Alice 25 # 1 Bob 30 # 2 Charlie 35

  5. How to save a Pandas DataFrame to a ZIP file with a specific filename?

    • Specify the desired CSV filename within the ZIP archive.
    df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Save DataFrame to ZIP with a specific CSV filename with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('people.csv', 'w') as f: df.to_csv(f, index=False)

  6. How to save a Pandas DataFrame to a ZIP archive in memory?

    • Use an in-memory bytes buffer to create a ZIP file and then write it to disk.
    import io df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Create ZIP in memory and write it to disk buffer = io.BytesIO() with zipfile.ZipFile(buffer, 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('data.csv', 'w') as f: df.to_csv(f, index=False) buffer.seek(0) with open('data.zip', 'wb') as f: f.write(buffer.read())

  7. How to save a Pandas DataFrame with a custom separator to a ZIP file?

    • Define a custom separator when saving the CSV file within the ZIP archive.
    df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Save DataFrame to CSV with a custom separator (e.g., semicolon) with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('data.csv', 'w') as f: df.to_csv(f, sep=';', index=False)

  8. How to save a Pandas DataFrame with specific encoding to a ZIP file?

    • Set the desired encoding when writing the CSV file.
    df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Save DataFrame with a specific encoding (e.g., UTF-8) with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: with zf.open('data.csv', 'w') as f: df.to_csv(f, index=False, encoding='utf-8')

  9. How to save a Pandas DataFrame to a password-protected ZIP file?

    • Use setpassword() to create a password-protected ZIP archive.
    df = pd.DataFrame({ 'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35], }) # Create a ZIP file and set a password with zipfile.ZipFile('data.zip', 'w', zipfile.ZIP_DEFLATED) as zf: zf.setpassword(b'secret') with zf.open('data.csv', 'w') as f: df.to_csv(f, index=False)

  10. How to extract a CSV file from a password-protected ZIP archive in Pandas?

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