Exploring public service requests made to the City of San Diego in R

Programs I write for my Data Mining course

We have data-set related to a particular show of a media company (like Hot star) and we need to predict the no of viewers (Regression Problem).

Electronic Sales Analysis using Pandas and Matplotlib.

This project was to create our designed AUC Catalog. It was divided into three phases; the first was to create the database design and the schema. The second phase was to scrape the original AUC catalog to collect the data we need and insert them into our database. The third phase was to create an API and a frontend to have a working website tha…

Contains tasks completed for CodeClan's dirty data project involving cleaning and tidying (very) messy data.

Mini project done as a part of TCS iON remote mentored internship.

Let us say you have 2 stocks A and B that may deliver the same result on average but exhibit different levels of risk, how would you compare them? This is where the Sharpe ratio comes into play.

⭐️Data Science/Data Analytics Projects⭐️

Data cleaning and SQL queries analyze pizza delivery data, cleaning tables such as customer_orders and runner_orders, and extracting insights like pizza order counts, customer preferences, runner performance, delivery times, and ingredient optimization from the dataset.

Jeopardy is a popular TV show in the US where participants answer questions to win money. It's been running for many years, and is a major force in popular culture. In this project, we'll work with a dataset of Jeopardy questions to figure out some patterns in the questions that could help you win.

In this project we will practice some machine learning workflow to predict a car's market price using its attributes.

Contains data on various IKEA products The main idea is to Perform Data Cleaning and Visualisation

Worked on a superstore dataset to help potential superstore owners make data driven decisions

In this end-to-end data analytics project, we have used cricket T20 world cup (2022) data to build insights on a best 11 players team that we can assemble from the earth . We used web scraping to collect data from espn cricinfo website then we performed some data transformation & cleaning in pandas, followed by building dashboards in Power BI.

This project aimed at cleaning the "Global Shark Attacks" dataset in order to analyze the fatality incidence in the records and the profile of these fatal attacks considering the 'sex', 'age', 'country' and 'year' information provided.

Explore Netflix's World 🌍🍿. An in-depth analysis of Netflix's vast content library! Dive into the data behind over 10,000 movies and TV shows. Discover trends, genres, top creators, and more with Python and data visualizations. Uncover the magic of Netflix data!

Explored and analyzed a diabetes dataset, implementing advanced data preprocessing techniques to handle missing values and visualize health metrics. Developed a predictive machine learning model using logistic regression to forecast diabetes occurrences with high accuracy.