In Python data analysis, how do I build a CLI?

In Python data analysis, building a Command Line Interface (CLI) can greatly enhance your data manipulation and analysis tasks. A CLI allows users to interact with the program directly from the terminal, providing an efficient way to execute data analysis scripts with various parameters.

Example of a Simple CLI in Python

# Import necessary libraries import argparse import pandas as pd def main(): # Create the parser parser = argparse.ArgumentParser(description='Perform data analysis on CSV files.') # Add arguments parser.add_argument('filepath', type=str, help='Path to the CSV file') parser.add_argument('--column', type=str, help='Column to analyze', required=True) # Parse the arguments args = parser.parse_args() # Read the CSV file data = pd.read_csv(args.filepath) # Perform some analysis if args.column in data.columns: print(data[args.column].describe()) else: print(f'Column {args.column} not found in CSV.') if __name__ == "__main__": main()

CLI Python data analysis argparse pandas

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