Working with messy, scattered data can feel overwhelming and frustrating, especially when you're trying to uncover meaningful insights. Without the right skills to organize and clean data, even simple tasks can become time-consuming and complicated. In this course, Data Import and Wrangling with R, you’ll gain the ability to import, clean, and combine datasets to prepare them for insightful analysis. First, you’ll explore how to import data from various sources, including local files, web URLs, and databases, while resolving common issues like missing values and inconsistent formats. Next, you’ll discover how to transform and tidy messy data using R packages like tidyr and dplyr. Finally, you’ll learn how to merge and combine datasets effectively, addressing challenges like duplicate entries and mismatched keys to create unified datasets for analysis. When you’re finished with this course, you’ll have the skills and knowledge of data import and wrangling in R needed to handle real-world data challenges and prepare datasets for meaningful analysis.
Overview
Working with messy, scattered data can feel overwhelming and frustrating, especially when you're trying to uncover meaningful insights. Without the right skills to organize and clean data, even simple tasks can become time-consuming and complicated. In this course, Data Import and Wrangling with R, you’ll gain the ability to import, clean, and combine datasets to prepare them for insightful analysis. First, you’ll explore how to import data from various sources, including local files, web URLs, and databases, while resolving common issues like missing values and inconsistent formats. Next, you’ll discover how to transform and tidy messy data using R packages like tidyr and dplyr. Finally, you’ll learn how to merge and combine datasets effectively, addressing challenges like duplicate entries and mismatched keys to create unified datasets for analysis. When you’re finished with this course, you’ll have the skills and knowledge of data import and wrangling in R needed to handle real-world data challenges and prepare datasets for meaningful analysis.
Taught by
Ana Voicu
