This R Studio Markdown aims to analyze data from 2020 of FBI's Hate Crime Statistics with various key parameters as control variables and defend hypotheses about hate crimes and bias motivation.

Demonstrating usage of Python and R in Jupyter Notebooks for data cleaning, manipulation, exploration, visualization, and modeling.

This repository contains all the pre-requisite notebooks for my internship as a Machine Learning Developer at Technocolabs. It includes some of the micro-courses from kaggle.

My DataCamp Project Notebooks

Writing PostgreSQL queries into jupyter notebook

This is a project experimenting with SQL queries in order to answer interesting questions about international debt using data from The World Bank.

Contains notebooks of projects carried out on the DataCamp platform

This repository contains pre-requisite notebooks regarding Pandas Library work for my internship as a Machine Learning Application Developer at Technocolabs.

Hey there, In this repository I will be Analyzing the Bitcoin Cryptocurrency Market. I have applied simple Data Manipulation and Data Visualization techniques. I have done this analysis using Jupyter Notebooks and Python Programming Language. Hope you get some insights about Data Manipulation!!

This repository contains finalized and working Jupyter Notebook files that encapsulate most of my work as an Analytics Intern with Stellar Solutions working for Space Systems Command.

This repository contains one of the pre-requisite notebooks for my internship as a Data Analyst at Technocolabs. It includes some of the micro-courses from Kaggle.

This Jupiter notebook covers basic CRUD operations (on MongoDB) using Python, loading a MongoDB Collection into a Pandas DataFrame and loading data from a .csv, .json and a RDBMS into MongoDB.

This notebook is part of a DataCamp competition. The challenge involves extracting relevant information about nutritional components from a food dataset and fitting a regression model to predict the calories of the foods.

Datacamp includes multiple Jupyter Notebooks (aka "projects"), this is a repo to show some of the work that's been done over there. It is specially useful for Data Cleaning, Manipulation and EDA.

In this notebook I will describe the process of scraping data from web portal understat.com that has a lot of statistical information about all games in top 5 European football leagues.

This Jupiter Notebook shows how to migrate data between a Pandas DataFrame and MySQL. It also shows how to manipulate data including writing queries like DDL and DML commands using Python. Libraries used are SQLAlchemy and sql.connector.

In this notebook US accidents database is analyzed. This is a countrywide car accident dataset, which covers 49 states of the USA. Information. The accident data are collected from February 2016 to March 2023(7.7 million records).

In this notebook, we're going to analyse the data that made Semmelweis discover the importance of handwashing. Let's start by looking at the data that made Semmelweis realize that something was wrong with the procedures at Vienna General Hospital.

The purpose of this project is to leverage the power of Python, in conjunction with Jupyter Notebook, to integrate movie reviews from The New York Times with comprehensive movie details from The Movie Database (TMDB). This integration provides a holistic view of movies, combining critical reviews with detailed metadata.

The purpose of this project is to analyze athletic sales data from 2020 and 2021 using Python within Jupyter Notebook. By combining, cleaning, and visualizing the data, we aim to uncover insights into regional sales patterns, retailer performance, and product trends. This analysis can be applied to retail businesses seeking to optimize sales.