Row and column indexing in R Programming

Introduction

Row and column indexing helps you pick specific parts of a table or matrix to look at or change.

You want to see just one row of data from a table.

You need to get a specific column from a dataset.

You want to change a value in a certain row and column.

You want to select multiple rows or columns to analyze.

You want to filter data based on row or column positions.

Syntax

R Programming

data[row_index, column_index]

Use numbers to pick rows and columns by position.

Leave row or column blank to select all in that dimension, like data[, 2] for all rows in column 2.

Examples

Selects the first row, all columns.

R Programming

data[1, ]

Selects all rows, third column.

R Programming

data[, 3]

Selects the value at row 2, column 4.

R Programming

data[2, 4]

Selects rows 1 to 3 and columns 2 and 4.

R Programming

data[1:3, c(2,4)]

Sample Program

This program creates a 3x4 matrix with numbers 1 to 12. Then it prints:

• The first row (all columns)
• The second column (all rows)
• The value at row 2, column 3
• Rows 1 and 2, columns 1 and 4

R Programming

data <- matrix(1:12, nrow=3, ncol=4)
print(data[1, ])
print(data[, 2])
print(data[2, 3])
print(data[1:2, c(1,4)])

Important Notes

Indexing starts at 1 in R, not 0 like some other languages.

You can use negative numbers to exclude rows or columns, e.g., data[-1, ] excludes the first row.

Use names instead of numbers if your data has row or column names, like data['row1', 'col2'].

Summary

Row and column indexing lets you pick parts of data by position.

Use data[row, column] with numbers or names.

Leaving row or column blank selects all in that dimension.