This ETL (Extract, Transform, Load) project employs several Python libraries, including Airflow, Soda, Polars, YData Profiling, DuckDB, Requests, Loguru, and Google Cloud to streamline the extraction, transformation, and loading of CSV datasets from the U.S. government's data repository at https://catalog.data.gov.

Comparison between several Python data profile libraries.

This repository contains interactive data dashboards generated for the Karnataka Police Datathon 2024. The analysis focuses on various aspects of accident data, including details about accused individuals, FIR insights, accident reports, complainant information, and victim insights.

This repository contains the code snippets, short and long scripts for EDA, and some useful libraries to save time.

This repository showcases my learning process of automating EDA using 'ydata-profiling'

Data profiling y-data profile, Data staging (Staging tables), Talend for ETL jobs, MySQL validations Dimensional model (Target tables), Facts and Dimensions, Mapping document explaining the source column name and where it finally maps to target column, Stage to Target, Document all transformations if any

The model predicts household energy usage using historical data and weather factors to optimize consumption and promote sustainability.

Data Profiler is a Streamlit app designed to provide insightful data analysis and visualization. Users can upload their datasets in '.csv' or '.xlsx' format, and the app generates a comprehensive profiling report using the YData Profiling library.

Creating quick visualizations and summary statistics using python

Read, Visualize, Automate and..