This data project on Python uncovers and visualizes untapped patterns regarding all Nobel Prize laureates up to date.

The objective is to analyze flight delays in the United States. Data from airlines, airports, and runways will be collected and processed. Machine learning models will be built using logistic regression, decision trees, and XGB classifiers. Visualizations will be created in Tableau, and Excel dashboards and SQL queries will be used for analysis.

This EDA focuses on uncovering intriguing patterns behind certain characteristics of the most popular songs on Spotify while assessing the degree to which such popularity is reflected also on YouTube.

An automation script for analyzing and processing CSV data, designed to identify and categorize errors by aggregators, and calculate totals, including a grand total. Developed to streamline data analysis at Infozillion Teletech BD Ltd.

Pandalyzer is a code-analysis tool for analyzing scripts written in Python using the Pandas data-manipulation library. The tool is still under development and supports only a subset of Python constructs and Pandas operations. It uses Abstract Interperation framework defined in my bachelor thesis: https://github.com/Hrubian/bachelor-thesis

This repository contains material related to the Pandas Learning.

Global companies analysis project based on 5 financial metrics to get an overview of market trends

This project is based on the nobel prize laureates. DataCamp datasets were used for this project.

We all are well aware about the Nobel prize. Here is an analysis of a dataset that tells about some of the insight information gathered.

This repository will be about data manipulation in Python and SQL.

An API-based python app for gathering and modifying information such as, most searched keyword in NAVER.

Used supervised learning regression technique to solve the business problem.

This is an end-to-end Data Analysis project using python and it's libraries pandas, numpy, matplotlib, seaborn. I have performed full data analysis steps on largest retail e-commerce orders dataset of Pakistan from problem statement to presenting report. It contains half a million transaction records from March 2016 to August 2018.

DSAI 201 Final Project

This project examines the crucial metrics around first serves, analyzing the differences between match winners and losers using an exploratory data analysis approach. I uncover patterns in serve percentages and effectiveness, providing insights into the pivotal role the first serve plays in determining match outcomes.