Data Wrangling and Transformation Portfolio

Overview

• Repository for cleaning, transforming, and preparing datasets for analysis.
• Includes Python scripts (pandas, numpy, re) files.

Featured Case Studies

1. 01_Badly_Structured_Data_Transformation

• Details: Fix poorly structured datasets and reformat for analysis.
• Dataset: Badly Structured Sales Data.xlsx

2. 02_Column_Split_and_Melt_Transformation

• Details: Transform wide data into tidy, long format using splits and melts.
• Dataset: Roadmap.xlsx

3. 03_Error_Detection_and_Cleaning

• Details: Identify and fix errors, remove duplicates, and handle missing values.
• Dataset: Hospital Data with Mixed Numbers and Characters.xlsx

4. 04_Split_and_Explode

• Details: Extract multi-value fields into separate rows using splitting and exploding.
• Dataset: Invoices-with-Merged-Categories-and-Merged-Amounts.xlsx

5. 05_Regex_Match_and_Split

• Details: Use regular expressions to identify, extract, and split patterns in data.
• Dataset: Jumbled-up-Customers-Details.xlsx

6. 06_Extract_From_Mixedup_Columns

• Details: Separate mixed data in single columns into distinct components.
• Dataset: Medicine-Data-with-lumped-Quantity-and-Measure.xlsx

Features

• Step-by-step techniques for common data challenges.
• Python and respective libraries (numpy, pandas, re)are used to complete tasks.
• Applicable to real-world datasets.

How to Use

1. Clone the repository:

   https://github.com/mayur-de/Data_Wrangling_and_Transformation.git

2. Install Python dependencies:

   pip install pandas numpy re

How to Contribute

• Contributions are welcome via pull requests.

License

• MIT License.