1. Data Wrangling with baseR
See what your basic R installation offers for data wrangling including the apply function family (
mapply) for loops and transformations, split, and combine (match, merge). Join datasets using
merge and compute summaries of your dataset using
2. Data Wrangling with dplyr
- data.frames and Tibbles
- Isolating Data with dplyr
- Deriving Information with dplyr
- Reshape Data
- Separate Columns
- Join Datasets
Learn to use the basic dplyr verbs to filter rows, select columns and sort/arrange datasets in combination with the pipe
%>% operator. Tidy your data with more complex transformations and apply various join operators.
3. Data Wrangling with data.table
Do assignments, joins and aggregations faster with data.table using various optimizations including keys and re-use of objects in memory (no copy).
Re-cap of the Grammar of Graphics implemented in ggplot2 syntax using geometric objects, aesthethic mappings and facet plots.
5. Data Wrangling Examples
Apply your data wrangling skills using a real and synthetic dataset to answer questions about your dataset quickly.