Real World Data Cleaning: Step-by-Step with Python Pandas!->
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About Dataset- 1.1 E-commerce Dataset with 30K Products. 1.2 This dataset is a collection of 30000 women fashion products. Categories covered in this dataset is western wear, Indian wear, perfumes and fragrances, watches and nightwear. ✨ 1.3 Column description is mentioned below- BrandName: Mentions the brand of the product Details: Deatils about the product Size: Sizes available MRP: This is max retail price SellPrice: This is the price after discount Category: Category of the product Nan value is null value
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I used kaggle API to download data from Kaggle.
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Unzipped data using Python since downloaded data was zipped Format.
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Used Python Pandas to read CSV data.
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Applied Some transformation as mentioned below- Change Column name finding null values in Dataset Deleting Null data from Dataset Deleting duplicate data from dataset Deleting useless Column from Dataset
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Use matplotlib library to analyze duplicate data into Dataset
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After transformation saved data into csv and excel format