🚒 🔥 Hobby data science project to analyze San Francisco's fire service.

CLI-runned EDA with 30 commands utilizing text-related functions, statistical calculations, data visualization, and data manipulation.

Python projects made for the freeCodeCamp Data Analysis with Python Certification.

The five projects that I worked on in the Data Analysis with Python course made by freeCodeCamp 🙌🏻

My freecodecamp Data Analysis with Python projects

A simple data analysis of a year worth of orders from a pizza restaurant with the goal of optimizing each week's ingredients

NYC TLC Data Analysis using Python, GCP Storage, Compute Engine, Mage Data Pipeline Tool, BigQuery, and Looker Studio. Aims to extract insights from the dataset for informed decisions and deeper operational understanding.

A data analysis project designed to empower the selection process of residential apartments from an HDB dataset to maximize comfort and livability

This is an EDA project that explores the Data Science Salaries in 2023 dataset. The purpose of this project is to gain insights into the current trends and patterns of salaries in the data science industry.

web application that provides visualizations and analysis of historical price data for various commodities

https://wc-goals.onrender.com/

Analysis on popular high protein foods

This Python for data analysis covers data analysis and text file creation, PyBank analysis, and PyPoll analysis. It showcases Python's capabilities in processing datasets, calculating summary statistics, and generating formatted outputs for financial and election data.

Using Python to analyze large datasets

Project aim is to make comprehensive and user-friendly solution for extracting, transforming, and visualizing data from the Phonepe pulse Github repository.

Identified and investigated fluctuations and patterns of tube temperatures on the London Underground network over an eight-year period, focusing on examining the various factors that influence tube temperatures and how they affect the overall temperature trends.

Python project demonstrating CSV module usage, file handling, variable storage, data structure iteration, and error handling.

This Python project utilizes pandas, numpy, seaborn, matplotlib, and plotly to analyze the Adidas sales dataset. By generating impactful visualizations and uncovering sales trends and correlations, the project aids retail stakeholders in making informed decisions.

Conducting stock market analysis