pandas - Read multiple parquet files in a folder and write to single csv file using python

Pandas - Read multiple parquet files in a folder and write to single csv file using python

To read multiple Parquet files from a folder and write them to a single CSV file using Python with Pandas, you can follow these steps. Pandas provides convenient functions to handle Parquet files using the pandas.read_parquet() function and to write to CSV files using the DataFrame.to_csv() method.

Steps:

  1. Import Libraries

    First, import the necessary libraries: Pandas for data manipulation and os for directory operations.

    import pandas as pd import os

  2. List Parquet Files

    Use os.listdir() to get a list of all Parquet files in a directory. Adjust the directory path (folder_path) to point to your specific folder containing the Parquet files.

    folder_path = '/path/to/parquet/files/' parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')]

  3. Read Parquet Files

    Iterate through the list of Parquet files, read each file using pd.read_parquet(), and store the DataFrames in a list (df_list).

    df_list = [] for file in parquet_files: df = pd.read_parquet(os.path.join(folder_path, file)) df_list.append(df)

  4. Concatenate DataFrames

    Concatenate the list of DataFrames (df_list) into a single DataFrame using pd.concat().

    combined_df = pd.concat(df_list, ignore_index=True)

  5. Write to CSV

    Finally, write the combined DataFrame to a single CSV file using to_csv() method.

    combined_df.to_csv('/path/to/output/combined_data.csv', index=False)

Full Example Code:

Here is how your complete Python script would look:

import pandas as pd import os # Step 1: List Parquet Files folder_path = '/path/to/parquet/files/' parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')] # Step 2: Read Parquet Files df_list = [] for file in parquet_files: df = pd.read_parquet(os.path.join(folder_path, file)) df_list.append(df) # Step 3: Concatenate DataFrames combined_df = pd.concat(df_list, ignore_index=True) # Step 4: Write to CSV output_csv = '/path/to/output/combined_data.csv' combined_df.to_csv(output_csv, index=False) print(f'Combined data saved to {output_csv}')

Notes:

  • Ensure that the folder_path points to the directory containing your Parquet files (*.parquet).
  • Adjust the output_csv variable to specify where you want to save the combined CSV file.
  • The pd.read_parquet() function automatically reads the Parquet file into a DataFrame.
  • pd.concat() concatenates multiple DataFrames along rows (axis=0 by default).
  • Use ignore_index=True in pd.concat() to reset the index of the concatenated DataFrame.
  • to_csv() method writes the DataFrame to a CSV file. Setting index=False ensures that the CSV file does not include the DataFrame index.

By following these steps, you can efficiently read multiple Parquet files from a folder, combine them into a single DataFrame, and then export the combined data to a CSV file using Pandas in Python.

Examples

  1. Pandas read multiple Parquet files into single CSV

    • Description: This query seeks code to read multiple Parquet files from a folder and combine them into a single CSV file using Pandas.
    • Code:
      import pandas as pd import glob # Path to the folder containing Parquet files folder_path = '/path/to/parquet/files/*.parquet' # Read all Parquet files into a single DataFrame all_files = glob.glob(folder_path) df = pd.concat([pd.read_parquet(f) for f in all_files], ignore_index=True) # Write combined data to CSV file df.to_csv('combined_data.csv', index=False)

  2. Python Pandas read Parquet files and export to single CSV

    • Description: This query looks for Python Pandas code to read multiple Parquet files and export their combined data to a single CSV file.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')] # Read Parquet files into a single DataFrame df = pd.concat([pd.read_parquet(os.path.join(folder_path, f)) for f in parquet_files], ignore_index=True) # Export combined data to CSV df.to_csv('combined_data.csv', index=False)

  3. Pandas concatenate Parquet files to CSV

    • Description: This query aims to concatenate multiple Parquet files from a folder into a single CSV file using Pandas.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')] # Read and concatenate Parquet files into a single DataFrame df = pd.concat([pd.read_parquet(os.path.join(folder_path, f)) for f in parquet_files], ignore_index=True) # Save combined data to CSV file df.to_csv('combined_data.csv', index=False)

  4. Python script to merge Parquet files into one CSV

    • Description: This query seeks a Python script to merge multiple Parquet files from a directory and save them as a single CSV file.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.parquet')] # Initialize an empty DataFrame combined_df = pd.DataFrame() # Read and concatenate all Parquet files into a single DataFrame for file in parquet_files: df = pd.read_parquet(file) combined_df = pd.concat([combined_df, df], ignore_index=True) # Export combined data to CSV combined_df.to_csv('combined_data.csv', index=False)

  5. Pandas merge multiple Parquet files into single CSV

    • Description: This query aims to merge multiple Parquet files located in a folder into a single CSV file using Pandas in Python.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')] # Read Parquet files into a single DataFrame df_list = [] for file in parquet_files: df_list.append(pd.read_parquet(os.path.join(folder_path, file))) combined_df = pd.concat(df_list, ignore_index=True) # Save combined data to CSV file combined_df.to_csv('combined_data.csv', index=False)

  6. Python Pandas read multiple Parquet files and merge to CSV

    • Description: This query seeks Python Pandas code to read several Parquet files and merge their contents into a single CSV file.
    • Code:
      import pandas as pd import glob # Path to the folder containing Parquet files folder_path = '/path/to/parquet/files/*.parquet' # Read all Parquet files into a single DataFrame all_files = glob.glob(folder_path) df = pd.concat([pd.read_parquet(f) for f in all_files], ignore_index=True) # Write combined data to CSV file df.to_csv('combined_data.csv', index=False)

  7. Pandas concatenate Parquet files and save as CSV

    • Description: This query looks for Pandas code to concatenate multiple Parquet files and save the combined data to a CSV file.
    • Code:
      import pandas as pd import glob # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # Get a list of all Parquet files all_files = glob.glob(folder_path + "*.parquet") # Read all Parquet files into a single DataFrame df = pd.concat((pd.read_parquet(file) for file in all_files), ignore_index=True) # Save combined data to CSV file df.to_csv('combined_data.csv', index=False)

  8. Python script to merge Parquet files and export to CSV

    • Description: This query seeks a Python script to merge multiple Parquet files from a folder into a single CSV file using Pandas.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.parquet')] # Initialize an empty DataFrame combined_df = pd.DataFrame() # Read and concatenate all Parquet files into a single DataFrame for file in parquet_files: df = pd.read_parquet(file) combined_df = pd.concat([combined_df, df], ignore_index=True) # Export combined data to CSV combined_df.to_csv('combined_data.csv', index=False)

  9. Pandas merge Parquet files from folder into CSV

    • Description: This query aims to merge multiple Parquet files from a directory into a single CSV file using Pandas in Python.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [f for f in os.listdir(folder_path) if f.endswith('.parquet')] # Read Parquet files into a single DataFrame df_list = [] for file in parquet_files: df_list.append(pd.read_parquet(os.path.join(folder_path, file))) combined_df = pd.concat(df_list, ignore_index=True) # Save combined data to CSV file combined_df.to_csv('combined_data.csv', index=False)

  10. Python Pandas read Parquet files and merge to single CSV

    • Description: This query seeks Python Pandas code to read multiple Parquet files from a folder and merge their contents into a single CSV file.
    • Code:
      import pandas as pd import os # Directory containing Parquet files folder_path = '/path/to/parquet/files/' # List all Parquet files in the directory parquet_files = [os.path.join(folder_path, f) for f in os.listdir(folder_path) if f.endswith('.parquet')] # Read Parquet files into a single DataFrame df = pd.concat([pd.read_parquet(file) for file in parquet_files], ignore_index=True) # Save combined data to CSV file df.to_csv('combined_data.csv', index=False)

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