This repository contains my completed projects for the Data Analysis with Python course by freeCodeCamp I've completed with the certification.
·Python
·Matplotlib
·Pandas
·NumPy
·SciPy
·Seaborn
Transforms a list of 9 numbers into a 3×3 matrix and computes mean, variance, standard deviation, max, min, and sum across rows, columns, and the entire matrix. Built with NumPy and designed with input validation.
This project analyzes demographic data from the U.S. Census dataset using Python and pandas and represents the following calculations:
·number of individuals in each race category
·average age of men
·percentage of people with a Bachelor's degree
·income statistics based on education level
·minimum weekly work hours and percentage of high earners among them
·country with the highest percentage of people earning >50K
·most common occupations in India
Processes and visualizes a dataset of medical examinations. Calculates BMI to classify patients as overweight, normalizes cholesterol and glucose data, and produces two visualizations:
Categorical Plot – compares health indicators between patients with and without cardiovascular disease. See result here
Heatmap – shows correlations between medical variables after filtering outliers. See result here
Analyzes daily page views from freeCodeCamp between May 2016 and December 2019, cleans the dataset(removes the top and bottom 2.5% of page views to eliminate extreme outliers and converts the date column into a datetime index for easier time-series handling) and creates visualizations(.png files) that highlight long-term trends and seasonal patterns in website traffic:
Line Plot - shows overall page views over time and highlights the long-term upward/downward trends. See result here
Bar Plot - displays the average monthly page views for each year and helps compare year-to-year performance. See result here
Box Plots - year-wise box plot shows how the distribution of page views changes over years and month-wise box plot reveals seasonal patterns across different months. See result here
