Welcome to our collaborative project aimed at processing data and converting it from CSV to JSON format for a Point of Sale (POS) system. Below are the detailed steps to achieve this task successfully:
Data Collection: Gather the CSV data containing relevant information for the POS system.
Data Cleansing: Use Python and libraries such as pandas and numpy to cleanse the data. This involves tasks like removing duplicates, handling missing values (NaN), and ensuring data consistency.
Data Validation: Validate the processed data to ensure its accuracy and integrity. Utilize pandas methods like head(), info(), describe(), and isnull() to gain insights into the dataset.
Data Transformation: Convert all object data types into integer format to prepare the data for further processing and analysis.
CSV to JSON Conversion: Once the data is cleansed and validated, it's time to convert it from CSV to JSON format.
Python Scripting: Write a Python script to read the processed CSV data and convert it into JSON format using libraries like csv and json.
JSON Output: Generate a JSON file containing the transformed data in a structured format suitable for integration with the POS system.
By following these step-by-step instructions, you'll be able to efficiently process the data, convert it from CSV to JSON format, and seamlessly integrate it into the POS system. Happy coding!