This repository contains code and data files for following along with the Data Analysis with Python course on freeCodeCamp. The project is organised into several directories, each focusing on different aspects of data analysis using Python.
The following folders contain projects that were made in order to gain the certification:
- mean-variance-standard-deviation-calculator: Contains a project that calculates statistical measures like the mean, variance, standard deviation, sum, max and min for a 3x3 matrix on the entire matrix, the 1st axis and 2nd. This also contains test cases for this code.
- demographic-data-analyser: Contains a project that analyses demographic data from the 1994 Census database using Pandas to answer various statistical questions about the dataset, such as the distribution of races, average age of men, education levels, and income statistics.
- medical-data-visualizer: Contains a project that analyses example medical data using Pandas to visualize differences between patients with and without cardiovascular disease and to visualize the correlations between all the different elements recorded during medical visits.
- page-view-time-series-visualizer: Contains a project that visualises time series data using a line chart, bar chart, and box plots to help understand the patterns in visits and identify yearly and monthly growth.
- sea-level-predictor: Contains a project that predicts the rise of sea levels based on the Global Average Absolute Sea Level Change, 1880-2014 from the US Environmental Protection Agency using linear regression. It predicts the rise based on data from 1880 then limits the predictions data from 2000 onwards due to the sharp increase during these years, then plots both of these on a scatter plot graph.
For each project above run the main.py file in the respective folder to run the test cases for the projects.
The following folders contain notes and exercises taken during the course:
- data-cleaning: Contains scripts for cleaning and preprocessing data.
- numpy: Contains scripts demonstrating various operations using the NumPy library.
- pandas: Contains scripts demonstrating data manipulation using the Pandas library.
- reading-data: Contains scripts demonstrating how to read different types of data files.
- RMOTR Data Science Curriculum: Contains exercises and data files for the RMOTR Data Science Curriculum.