AMMnet Hackathon Session 2: Introduction to Data Wrangling in R

This tutorial introduces you to data wrangling. By data wrangling, we mean here the process of checking and correcting quality and integrity of data relevant to malaria modeling, prior to any further analysis. This is also known as data validation. Data validation involves checking various aspects of your dataset, such as missing values, data types, outliers, and adherence to specific rules or constraints. Validating our data helps maintain its quality and integrity, ensuring that any analyses or decisions made based on the data are robust and reliable.

The AMMnet Hackathon blog is a continual support space that anyone can access to learn how to code and how to code better, to upskill people from a distance and improve abilities in data handling, presentation and analysis, experimental design, quantitative understanding, coding and problem solving and transmission modelling.