Contains tasks completed for CodeClan's dirty data project involving cleaning and tidying (very) messy data.
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Updated
Apr 4, 2022 - HTML
Contains tasks completed for CodeClan's dirty data project involving cleaning and tidying (very) messy data.
A Heart Diseases Prediction built using Django web applications. Users can check whether it suffer heart diseases or not.
An analysis of Seattle rain data collected at SeaTac International Airport from 1948 to 2017. *PLEASE SEE README.MD BELOW FOR THE FULL REPORT*
Data preprocessing & Data cleaning project
Learning Material for the Computer Language Workshop, Fall 2018, Economics Department, The New School for Social Research. This only covers the first half of the class, which I taught.
Automate the process of EDA and Data Cleaning
Explore global drug seizures from 1980 to 2020 through our data analysis project. We delve into drug confiscation data, revealing trends, hotspots, and the evolution of seized drug types. Using visualization, analysis, and dashboards, we provide insights into the fight against drug trafficking.
A case study about a bike-share company to help understand the difference between different users
Performing Data Wrangling (gathering, assessing, cleaning) of WeRateDogs Twitter account & archive using Jupyter Notebook, followed by storing, analyzing and visualizing the wrangled data.
Fundamental R skills. From importing and transforming data to mastering relational data and data visualization, these challenges offer hands-on experience for a robust foundation in R.
We have to keep adress content from any given html file and remove as much other content from the input html as possible.
A collection of 'dirty' datasets that I cleaned and analysed
Scraping different products and thereafter analyzing different aspects respective to the products.
A case study I completed as part of the final course in the Google Data Analytics Professional Certificate program on Coursera. *PLEASE SEE README.MD BELOW FOR THE FULL REPORT*
For the kaggle project - Loan Interest Rate Prediction, the repository contains the deployment details, project documentation file and project link.
Using R to perform Multiple linear regression (R) on a used car prices dataset.
Data management tools for R as inspired by Stata, SPSS, and other statistical software.
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