Data in R

This section is on data handling and data manipulation in R. The range of areas covered includes the following.

Data Objects

• Data Types: These include introduction to R data types such as numeric (or double), integer, character, logical, complex and raw.

• Data Structures: These include introduction to the main data structures, which are vectors, matrices, arrays, dataframes, and lists.

Read & Write Files

• Read or Write Files: These include discussions on how to read or import files from, or write and export data to CSV, TXT, Excel files, and file formats from common statistical packages such as R, SPSS, SAS, and STATA.

Data Handling

• Aggregate Data: These include discussions on how to aggregate data using the colSums(), rowSums(), colMeans(), rowMeans(), sapply(), apply(), and aggregate() functions.

• Basic Data Operations: These include discussions on basic data operations using functions such as sort(), rev(), unique(), duplicated(), rank(), head() and tail().

• Contingency Tables (Two-way Frequency Table): These include discussions on how to create contingency tables using the table() and xtabs() functions.

• Deleting or Naming Columns and Rows: These include discussions on how to delete, name or rename columns and rows of data objects using the subset(), colnames() and rownames() functions.

• Frequency Tables: These include discussions on how to create frequency tables using the table(), xtabs() and cut() functions.

• Merge or Combine Data: These include discussions on how to merge or combine dataframes, columns or vectors, matrices and lists using the merge(), rbind(), and cbind() functions.

• Reshape and Splitting: These include discussions on how to reshape, split and unsplit data objects using the reshape(), split() and unsplit() functions.

• Subsetting and Filtering Data: These include discussions on how to subset or filter a column or vector, dataframe, and matrix using the subset() and which() functions.