In this project, I cleaned Housing data in SQLite. This included filling in null values, splitting columns into appropriate sub-columns, removing duplicates as well as obsolete columns.
View Project
In this project, I used a vast dataset which updates daily. The dataset was provided by Our World In Data and can be found by clicking here. I looked at particular features of the data to determine proportion of the countries that got the virus, calculating infection rates, looking at infection rates per continent as well as working with time series data. I also looked in detail at vaccination rates. My visualizations for this project can be found in my Tableau public page below.
View Project
These projects are more geared towards Data Science since they incorporate Machine Learning libaries such as scikit-learn.
Using Supervised Learning to classify tweets as being as from New York, London or Paris. I also used K-Nearest Neighbor to predict whether a tweet will go viral.
View Project
This dataset was sourced from Kaggle. The analysis looked at which channel has the most trending videos, which time of the day are trending videos most likely to be published and finally asked the question - can a video's number of likes be predicted from the number of views and number of comments using Multiple Linear Regression?
View Project
Analyzing data and communicating findings about endangered species. Data from the National Parks Service.
View Project
Looking at the correlation between GDP and life expectancy in Chile, China, Germany, USA, Mexico and Zimbabwe.
View Project