cafe-sales-data-cleaning

Cafe Sales Data Cleaning Project

Here, I Need to Clean the Dataset which is dirty

dirtydataset nothing but the calues of calaculated columns or any values which are error or unknows i need to fill those error and unknown values with the help of numpy and numerical calculations

• PROJECT GOALS

• Handle missing or incorrect values in both numeric and text data

• Create clean, consistent datasets ready for analysis and modeling

• FILES INCLUDED:-

• | File Name | Description
  dirty_cafe_sales.csv | Original raw dataset (optional)
  clean_numeric.py | Script to clean numeric data
  cleaned_numeric_data.csv | Cleaned numeric data
  clean_text.py | Script to clean text columns cleaned_cafe_sales_text.csv | Cleaned text/categorical data
  final_cleaned_data.csv | Fully cleaned and merged dataset

• Cleaning Process

• Replaced NaN, ERROR, UNKNOWN in numeric columns using formulas.

• Replaced dirty text values (UNKNOWN, ERROR) with "Missing"

• TOOLS USED

• Python

• Numpy

• Pycharm(IDE)

• #next Steps

• Script to normalize numerical fields and Final normalized output for ML

• #Author

• SURYADEV05

• B.Tech CSE(AIML)

• Email:-suryatt.05@gmail.com

• Linkedin:-https://www.linkedin.com/in/thirukkovalluru-surya-teja-6771922bb/