R CODER

DATA TRANSFORMATION IN R

Data transformation involves techniques to filter data according to specific conditions, segment data into smaller groups, sort data according to defined criteria, summarize data by calculating sums or averages, and combine different data sets into a single data set

BASE R

With base R, data manipulation tasks can be performed without relying on external packages, offering a robust set of tools to work with data sets efficiently, allowing various operations such as data selection, filtering, transformation and summarization

Row and column names in R

Row and column names

rownames() colnames() dimnames()

Learn how to subset data in R with square brackets and the subset function

Subset data based on conditions

subset() $ [] [[]]

The table() and prop.table() functions in R

Absolute/relative frequency and contingency tables

table() prop.table() xtabs() addmargins()

Categorize data in R with the cut function

Categorize numerical data

cut()

Learn how to split data in R

Split data based on groups

split() unsplit()

Learn how to use the aggregate function in R

Aggregate data

aggregate()

colSums, rowSums, colMeans and rowMeans functions in R

Row and column sums and means

rowSums() colSums() rowMeans() colMeans()

rbind() and cbind() functions in R

rbind() and cbind() functions

rbind() cbind()

Join data frames in R with the merge function

Merge data frames

merge()

DPLYR PACKAGE

dplyr offers a clear and concise syntax to perform common tasks such as filtering, selecting, grouping and merging data, being a more intuitive and efficient alternative to R base functions for data manipulation operations

Select columns in R with dplyr

Select columns with dplyr

select() contains() where() matches() starts_with() ends_with() all_of() any_of()

Filter rows in R with dplyr

Filter rows with dplyr

filter() slice()

Order rows in R with dplyr

Order rows with the arrange() function from dplyr

arrange() desc()

Rename columns in R with dplyr

Rename columns with the rename() function from dplyr

rename() rename_with()

Create and modify columns in R with dplyr

Create and modify columns with the mutate() function from dplyr

mutate() across()

The summarise() function from dplyr

Create statistical summaries with the summarise() function from dplyr

summarise() group_by()