https://github.com/anuppm9917/data-processing-and-csv-to-json-using-python-project

This project guides you through processing data from CSV to JSON format using Python. You'll learn to cleanse, validate, and transform data with pandas, numpy, csv, and json libraries, ensuring it's ready for POS system integration. This will help improve data integrity and streamline integration.
https://github.com/anuppm9917/data-processing-and-csv-to-json-using-python-project

csv-files data data-analysis data-cleaning data-collection data-transformation data-validation python3 transformation

Last synced: 4 days ago
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This project guides you through processing data from CSV to JSON format using Python. You'll learn to cleanse, validate, and transform data with pandas, numpy, csv, and json libraries, ensuring it's ready for POS system integration. This will help improve data integrity and streamline integration.

• Host: GitHub
• URL: https://github.com/anuppm9917/data-processing-and-csv-to-json-using-python-project
• Owner: anuppm9917
• Created: 2024-04-14T11:48:13.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-06-06T14:48:36.000Z (8 months ago)
• Last Synced: 2024-06-06T16:33:11.810Z (8 months ago)
• Topics: csv-files, data, data-analysis, data-cleaning, data-collection, data-transformation, data-validation, python3, transformation
• Language: Python
• Homepage:
• Size: 157 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Data-Processing-and-CSV-to-JSON-using-Python

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:

# Step 1: Data Processing

**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.

# Step 2: Convert CSV to JSON

**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.

# Conclusion:

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!