Gym Check-ins and User Metadata
Dataset: Gym Check-ins and User Metadata: https://www.kaggle.com/datasets/mexwell/gym-check-ins-and-user-metadata
Overview: This dataset contains information on user check-ins at different gym locations, along with related user metadata. The data is relatively clean and was used to practice building data models, standardizing fields, and extracting and querying information across multiple tables for analysis and visualization purposes. The focus was on performing various analyses and creating insights based on the gym check-in data.
Tools used: MySQL, Tableau
Real Estate Sales 2001-2023
Dataset: Real Estate Sales 2001-2023: https://catalog.data.gov/dataset/real-estate-sales-2001-2018
Overview: This dataset, sourced from data.gov, contains over 1 million rows of real estate sales data spanning 21 years. It was utilized to clean and transform data using pandas, addressing null values, resolving inconsistencies, and detecting outliers through statistical analysis and visualization. Exploratory Data Analysis (EDA) was conducted using Matplotlib and Seaborn to plot and analyze distributions, patterns, and trends, yielding insights based on metrics and distribution theory.
Tools used: Python
