R library for spatial data analysis based on libgeoda and GeoDa

Scraped job description and leveraged the concepts of Natural Language Processing (NLP) and GloVe Algorithm to extract the keywords through data and performed analysis. Presenting the vital keywords from data analyst job summary from the Indeed website..

My R Assignments & Case Studies from PGDDA course

A new feature selection algorithm based on relevance, redundancy and complementarity (A Research Paper Implementation)

The repository contains a Pune house price prediction system build using R programming Language. The System efficiently calculates and analyze house prices in multiple areas across Pune using machine learning models and Data science and analytical tools

This project is all about how to collect data from a webpage and to analyze or visualize it in R.The data is scraped from Wikipedia which includes the Obesity report of USA.

iSLS10 data analysis workshop

Files with the realtime API covid 19 data for analysis and visualization. It works with Realtime-Api for data ingestion. So when running -> refersh the code once and run . Fist run "covid-world.R "file ,contains the main source code for files with detail comments on each code written for better understanding

First Project- Bellabeat Case Study, Google Data Analytics Capstone

This Project is all about studying and analyzing the Urbanization Rates and the percentage of Population living in Urban Areas for the Countries.

Combining all work done in the Udemy course R Programming A-Z

Performed Exploratory Data Analysis (EDA), Data Cleaning, Data Visualization such as bargraph, Histogram and Heatmap etc. using ggplot2 in R Programming (R studio)

Crime Data Analysis for ANLY 506-90

The National Emissions Inventory (NEI) is a detailed estimate of air emissions that include criteria pollutants and hazardous air pollutants. Fine particulate matter (PM2.5) is an ambient air pollutant for which there is strong evidence that it is harmful to human health.

iSLS9 data analysis workshop

This case study demonstrates the power of R for analyzing customer satisfaction data. R can be used to perform various analyses, from EDA to hypothesis testing, and can help businesses gain valuable insights into customer satisfaction.

This project is part of the HarvardX course PH125.9x Data Science: Capstone Project.

Portfolio of work submitted for SQA qualification Data Science, SCQF 8

Helper functions which I've created to avoid rewriting the same functions all the time.