Power Query Practice in Power BI

Welcome to the Power Query Practice repository! This project is focused on various data cleaning techniques using Power Query in Power BI.

Project Overview

In this project, we perform the following tasks:

1. Column Profiling: Understanding the data types and distribution of values in each column.
2. Dealing with Missing Values: Identifying and handling empty or blank values.
3. Encoding Nulls: Converting null values into a format suitable for analysis.
4. Imputing Missing Values: Replacing missing values with appropriate substitutes.
5. Working with Dates: Cleaning and formatting date values.
6. Adding New Columns: Creating new columns based on existing data.
7. Splitting / Extracting Data: Dividing columns into multiple parts or extracting specific data.
8. Extracting First Item: Extracting the first item from lists or text strings.
9. Text / Sentiment Analysis: Performing basic text analysis and sentiment evaluation.
10. Filtering Unnecessary Data: Removing irrelevant rows or columns to streamline the dataset.

Data Source

To follow along with this project, download the sample data from Kaggle:

📁 Download Sample Data

How to Use This Repository

Clone the Repository

First, clone the repository to your local machine:

git clone https://github.com/MasterMindRomii/Data-Cleaning-Using-Power-Query
cd Data-Cleaning-Using-Power-Query