Project Description:
Performed an exploratory data analysis on the most streamed Spotify songs of 2023 using Python and various libraries such as pandas, matplotlib, seaborn.
Visualized the distribution of song attributes such as popularity, duration, loudness, tempo, and energy using histograms, boxplots, and scatterplots.
Identified the top 10 artists and songs based on popularity and streaming counts using bar charts.
Project Description:
Performed an exploratory data analysis on the Karachi houses dataset using Python and various libraries such as pandas, matplotlib, seaborn.
Visualized the distribution of house attributes such as price, area, and location using histograms, boxplots, and scatterplots..
Identified Top 10 locations based on price using bar chart.
Project Description:
Performed an exploratory data analysis on the mobile prices in Pakistan dataset using Python and various libraries such as pandas, matplotlib, seaborn.
Identified the most popular and expensive brands, models, and features of mobiles using descriptive statistics and groupby operations.
Project Description:
Performed an exploratory data analysis on the ODI men’s cricket match data using Python and various libraries such as pandas, matplotlib, seaborn.
visualized the distribution of match attributes such as runs, wickets, overs, toss, and result using histograms, bar charts, and line charts.
Project Description:
Performed an exploratory data analysis on the Pakistan employment dataset using Python and various libraries such as pandas, matplotlib, seaborn.
Visualized the distribution of employment using histogram and bar charts.
Project Description:
Performed an exploratory data analysis on the Pakistan used car dataset using Python and various libraries such as pandas, matplotlib, seaborn.
Visualized the distribution of car attributes such as price, year, mileage, fuel, engine, and transmission using histograms, bar charts, and pie charts.
Identified the most popular and expensive brands, models, and features of used cars in Pakistan using descriptive statistics and groupby operations.