Reading multiple files contained in a zip file with pandas

Reading multiple files contained in a zip file with pandas

You can read multiple files contained in a zip file using pandas by leveraging the zipfile module to extract the files from the zip archive and then using pandas to read each extracted file. Here's how you can do it:

import zipfile import pandas as pd # Specify the path to the zip file zip_file_path = 'path/to/your/zipfile.zip' # Open the zip file with zipfile.ZipFile(zip_file_path, 'r') as zip_ref: # Get a list of filenames in the zip archive file_list = zip_ref.namelist() # Iterate through each filename and read the corresponding file with pandas for filename in file_list: # Extract the file from the zip archive zip_ref.extract(filename, path='temp_extracted_folder') # Read the extracted file using pandas extracted_file_path = f'temp_extracted_folder/{filename}' df = pd.read_csv(extracted_file_path) # Adjust the read function for different file formats # Process the data or perform analysis on df # Optional: Remove the extracted file if needed # import os # os.remove(extracted_file_path) # Optional: Remove the temporary extracted folder # import shutil # shutil.rmtree('temp_extracted_folder')

In this example:

  • Replace 'path/to/your/zipfile.zip' with the actual path to your zip file.
  • The zip_ref.namelist() method is used to get a list of filenames contained in the zip archive.
  • The loop iterates through each filename, extracts the corresponding file, and then reads it using pandas.
  • You can adjust the read function (pd.read_csv, pd.read_excel, etc.) based on the format of the files you're extracting.
  • After processing each file, you can optionally remove the extracted files and the temporary folder.

Make sure to handle any specific requirements based on the contents of your zip file and the type of data you're working with.

Examples

  1. Reading Multiple CSV Files from a Zip Archive in Pandas

    • This snippet demonstrates how to open a zip file and read multiple CSV files using pandas.
    # Install pandas if needed !pip install pandas 
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # List all files in the zip file_list = zip_ref.namelist() # Read all CSV files in the zip into separate DataFrames dataframes = {name: pd.read_csv(zip_ref.open(name)) for name in file_list if name.endswith(".csv")} print("Loaded DataFrames:", dataframes.keys())

  2. Reading Specific Files from a Zip Archive with Pandas

    • This snippet demonstrates how to read specific files from a zip archive by name or pattern.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read a specific file df = pd.read_csv(zip_ref.open("important_data.csv")) print("Data from important_data.csv:", df.head())

  3. Reading Multiple Excel Files from a Zip Archive with Pandas

    • This snippet shows how to read multiple Excel files from a zip archive.
    # Install pandas and openpyxl if needed !pip install pandas openpyxl 
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # List all Excel files in the zip file_list = [name for name in zip_ref.namelist() if name.endswith(".xlsx")] # Read all Excel files into separate DataFrames dataframes = {name: pd.read_excel(zip_ref.open(name)) for name in file_list} print("Loaded Excel DataFrames:", dataframes.keys())

  4. Combining DataFrames from a Zip Archive in Pandas

    • This snippet demonstrates how to read multiple CSV files from a zip archive and combine them into a single DataFrame.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read and combine CSV files into a single DataFrame combined_df = pd.concat([pd.read_csv(zip_ref.open(name)) for name in zip_ref.namelist() if name.endswith(".csv")]) print("Combined DataFrame:") print(combined_df.head())

  5. Reading JSON Files from a Zip Archive with Pandas

    • This snippet shows how to read JSON files from a zip archive into Pandas DataFrames.
    # Install pandas if needed !pip install pandas 
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read all JSON files in the zip into separate DataFrames dataframes = {name: pd.read_json(zip_ref.open(name)) for name in zip_ref.namelist() if name.endswith(".json")} print("Loaded JSON DataFrames:", dataframes.keys())

  6. Filtering Files in a Zip Archive with Pandas

    • This snippet demonstrates how to read and filter files from a zip archive based on custom criteria.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read and filter CSV files based on custom criteria filtered_dfs = {name: pd.read_csv(zip_ref.open(name)) for name in zip_ref.namelist() if "sales" in name} print("Filtered DataFrames:") print(list(filtered_dfs.keys()))

  7. Validating Files in a Zip Archive with Pandas

    • This snippet demonstrates how to validate the structure of CSV files in a zip archive before reading them into Pandas.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Validate and read CSV files dataframes = {} for name in zip_ref.namelist(): if name.endswith(".csv"): df = pd.read_csv(zip_ref.open(name)) # Ensure required columns are present if {"Name", "Age"} <= set(df.columns): dataframes[name] = df else: print(f"Invalid structure in {name}") print("Validated DataFrames:") print(list(dataframes.keys()))

  8. Processing DataFrames from a Zip Archive in Pandas

    • This snippet shows how to apply processing to DataFrames read from a zip archive.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read CSV files dataframes = {name: pd.read_csv(zip_ref.open(name)) for name in zip_ref.namelist() if name.endswith(".csv")} # Process the dataframes (e.g., fill missing values) for name, df in dataframes.items(): df.fillna(0, inplace=True) print("Processed DataFrames:") print(dataframes)

  9. Reading Compressed CSV Files from a Zip Archive in Pandas

    • This snippet demonstrates how to read compressed CSV files from a zip archive with Pandas.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Read compressed CSV files compressed_dfs = {name: pd.read_csv(zip_ref.open(name), compression="zip") for name in zip_ref.namelist() if name.endswith(".zip")} print("Compressed CSV DataFrames:") print(compressed_dfs)

  10. Creating a DataFrame from Zip Archive Metadata

    • This snippet shows how to create a DataFrame containing metadata (like filenames and sizes) from a zip archive.
    import pandas as pd import zipfile # Open the zip file with zipfile.ZipFile("data.zip", "r") as zip_ref: # Get metadata for all files in the zip metadata = [{"Filename": info.filename, "Size": info.file_size} for info in zip_ref.infolist()] metadata_df = pd.DataFrame(metadata) print("Zip Metadata DataFrame:") print(metadata_df)

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