This folder contains work I submitted as part of the technical interview for a data science position at CEMA
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Updated
Aug 11, 2023 - HTML
This folder contains work I submitted as part of the technical interview for a data science position at CEMA
I finished the Woz U's Data Science program in March 2022. This is the code and the projects that I turned in during my student experience.
A analysis of the gender pay data across Scottish companies
This project utilizes R to preprocess Spotify's "Unpopular Songs" and "Genre of Artists" datasets from Kaggle. Following tidy data principles, it handles duplicates, transforms variables, scans for outliers, and normalizes data. The resulting clean dataset is ready for statistical analysis, ensuring accurate and ethical data practices.
SQL and dplyr queries; basic descriptive statistics mapping
Udacity Nano degree Project 5. (Communicate Data Findings)
Analysis of NOAA storm database with R to determine most severe types of weather event
This folder contains R training material (codes and sample datasets).
wrangle and get insights from tdv_movies dataset
This project is aimed to use data munging techniques, such as assessing the quality of the data for validity, accuracy, completeness, consistency and uniformity, to clean the OpenStreetMap data for a part of the world.
This project which is known as 'wrangle and analyze data' involves the wrangling of WeRateDogs twitter archive data from the period of 2015 to 2017
Exploratory analysis of the soccer database
Gathering, assessing, cleaning and analyzing the data for twitter archive WeRateDogs
Data wrangling and analytics of housing trainings dataset from Arifu.
This project includes 5th project of udacity nanodegree program.
A collection of 'dirty' datasets that I cleaned and analysed
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