Graduate with major in Statistics and skilled in MS-Excel, SQL and python.
Knows basic Tableau and Machine Learning.
Cleaned geographical data which was provided as a part of the Capstone project by Infinite Analytics. The dataset had large amounts of addresses missing which were retained by reverse geocoding using OpenStreetMap and python libraries.
Worked on COVID-19 data available freely across the internet and performed exploratory data analysis to convert chunks of numbers into summarising tables which are easily interpretable.
This is an extension of the COVID-19 Data Exploration project. After saving the output tables of SQL queries as excel files, I imported the data in Tableau and built some interesting visualisations out of it. I recommend downloading and opening the file on desktop version as the formatting changes drastically in web view.
This small project contains queries written in MS SQL server intended to clean the Nashville Housing dataset. I performed various operations such as populating NULL values, removing duplicates, cleaning the addresses, dropping unimportant columns to make the dataset more meaningful for further analysis.
This project is built around dataset which contains star ratings, reviews, actual price , discount offer, etc. on products on E-commerce websites like Flipkart and Amazon. I started out with running exploratory data analysis on the given dataset to deal with null values and visualised the distributions of different features. Then I imputed some null values and corrected some inconsistencies in data. At last I trained my Machine learning model (XGB Regressor) and fine tuned its parameters to get good predictions.This was a part of a my first Hackathon and I ended up in top 20% of the participiants.
This small project is to demonstrate my understanding of Pivot tables and Creating small dashboards in Excel. Not only does this project focuses on Pivot tables and slicers, It also contains some level of data cleaning to make it more interpretable.