This repository contains summaries of the projects completed as part of the Data Fundamentals Nanodegree program by Udacity.
The objective was to interpret a Tableau dashboard titled "Madrid in Detail" to derive three significant insights about the city of Madrid.
Real-life data from the New York Stock Exchange (NYSE) was analyzed. The dataset contains historical financial data from S&P 500 companies. The main objectives were to calculate summary statistics, draw inferences, calculate business metrics, and forecast future growth prospects for the companies.
Python was used to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. Descriptive statistics were computed, and an interactive terminal-based script was developed to present the statistics.
The project involved analyzing a dataset using NumPy, Pandas, and Matplotlib to gain insights into factors influencing patient attendance at medical appointments. The "No-show appointments" dataset from Kaggle was used for analysis.
Feel free to explore each project for more details!