Data_Analyst_Portfolio

Table of Contents

• Introduction

• FIFA 21 Players Analysis

• Stack Overflow Annual Developer Survey Analysis

• London Bike Sharing Data Analysis & Visualization

• Tools & Technologies

• Data Sources

• Additional Power BI Projects

  • Power BI Interactive Sales Analytics Project

• Additional SQL Projects

  • SQL Murder Mystery

Introduction

Welcome to my Data Analyst portfolio!

This repository contains a collection of insightful data analyses, and showcases my skills through a variety of projects:

Project 1: Data Cleaning & Transformation (P_1)

FIFA 21 Players Analysis:

Dive into a comprehensive data cleaning and transformation project that takes a messy "FIFA 21" dataset and turns it into a structured, insightful resource. FIFA 21 is a popular video game that simulates soccer matches. Often, data collected from this game might be messy, containing inconsistencies, missing values, and various formatting issues.

• Highlights:

  • In this project, I focused on cleaning and preparing messi FIFA 21 data for analysis using Python and Pandas.
  • Cleaned and standardized player data, discovered performance trends, and created Dashboard using Power BI.
  Fifa21.Players.Analysis.mp4

Project 2: Data Analysis (P_2)

Stack Overflow Annual Developer Survey Analysis

Delve into the rich data of the "Stack Overflow Annual Developer Survey 2022", uncovering trends, preferences, and valuable insights within the vibrant developer community. This analysis was conducted using Python, leveraging powerful libraries such as Pandas, Matplotlib, and Seaborn.

• Key Insights:
  • Impact of Remote Work: The survey reveals the evolving landscape of work preferences among developers,
    • Fully remote: 42.98%
    • Hybrid (some remote, some in-person): 42.44%
    • Full in-person: 14.58%
  • Learning to Code Trends: The most popular learning method is 'School (i.e., University, College, etc)', with 3669 responses.
  • Demographics:
    • Age Distribution: The majority of survey respondents fall within the 25-34 age group.
    • Gender Distribution: The survey reflects a gender distribution of responses as follows,
      • Male: 90% (64607 responses)
      • Female: 5% (3399 responses)
      • Others: Remaining percentage
    • Geographical Distribution: A significant portion of responses originate from the USA, with over 14.5k responses.
  • Professions in Demand: Analysis points to Full Stack Developer as the most popular profession in 2022, with a notable 30000+ responses.
  • Popular Programming Languages: In the year 2022, JavaScript emerges as the top-ranking language among developers, indicating its enduring popularity and utility.

Project 3: Data Visualization (P_3)

London Bike Sharing Data Analysis & Visualization

This project delves into the determinants of cycling demand in London, shedding light on patterns such as peak usage by day, month, weather conditions, and seasonal variations.

• Key Insights:
  • Bike Sharing by Day: Higher activity on Tuesdays, Wednesdays, and Thursdays.
  • Bike Sharing by Month: Summer months exhibit increased usage compared to winter.
  • Bike Sharing on Holidays: More activity on non-holiday days.
  • Bike Sharing on Weekends: Weekdays show higher usage than weekends.
  • Bike Sharing by Season: Summer emerges as the peak season for bike usage.
  • Peak Hours by Season: Evening hours (5pm-6pm) and morning hours (8am) noted as peak times during different seasons.
  • Weather Impact on Bike Usage:
    • "Clear" weather sees the highest rentals, followed by "scattered clouds" and "broken clouds".
    • Surprisingly, more bikes are rented on rainy days compared to cloudy days.
  • Demand Patterns:
    • Higher demand on working days, particularly during clear weather.

Tools & Technologies

The projects in this repository were developed using Python, Jupyter Notebook, Pandas, Matplotlib, Seaborn, Power BI

Data Sources

The data used in these projects was sourced from Kaggle

If you're interested in exploring more of my work, don't forget to check out my other projects, including additional Power BI projects, listed above.

Feel free to explore these projects and reach out if you have any questions or collaboration opportunities.