The mark of quality and trust for open data

This is Udacity's Data Analyst Nanodegree's 5th project; which is Wrangling and Analyzing WeRateDogs Twitter account.

Wrangle and Analyze Data of twitter WeRateDogs account

This repository provides R scripts for reproducing virtual species generating, modeling species distribution and final figures related with published manuscript.

It was the project of the udacity data analysis nano degree, my job was to gather data from Twitter API programmatically with python then assess it and discover its quality and tidiness issues then clean these issues with pandas and finally, I did some analysis and visualization to this data to make insights of it

A virtual Internship introduced by KPMG AU on Forage.

Step by step Guide to data assessment, cleaning and analysis using a hypothetical phase II clinical trial dataset in Python

This repository has the Udacity data wrangling exercise, which helps us practice the wrangling process.

This report details the steps employed for wrangling the data used in the "WeRateDogs" project. The three steps in the wrangling phase of data analysis – gathering, assessing, and cleaning – were strictly followed.

Generates a match score of two person names from 0-100, where 100 is the highest, on how closely two individual full names match. The scoring is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge

This repo contains files that show the different steps in data wrangling - gathering, assessment and cleaning. The use case is to wrangle data for WeRateDogs twitter account.

Data gathering, Assessing and cleaning on audible dataset