Subset Data Frames in R
Subsetting or filtering the Data Frames is an essential part of data analysis. In this article, you will learn how to subset Data Frames in R.
First, create a sample Data Frame
df <- data.frame(col1 = c("A", "B", "C", "D", "E"),
col2 = c(1, 2, 3, 4, 5),
col3 = c(0.1, 0.2, 0.3, 0.4, 0.5),
col4 = c("abc", "def", "xyz", "lmn", "pqr"))
df
# output
col1 col2 col3 col4
1 A 1 0.1 abc
2 B 2 0.2 def
3 C 3 0.3 xyz
4 D 4 0.4 lmn
5 E 5 0.5 pqr
Subset Data Frame based on columns
The Data Frame df contains four columns (col1, col2, col3, col4). Subset df to contain only col2 and
col4 columns,
Using column indexes,
df[, c(2, 4)]
# output
col2 col4
1 1 abc
2 2 def
3 3 xyz
4 4 lmn
5 5 pqr
Using column names,
df[, c("col2", "col4")]
# output
col2 col4
1 1 abc
2 2 def
3 3 xyz
4 4 lmn
5 5 pqr
You can also use subset function to subset Data Frame,
subset(df, select=c(2, 4))
# output
col2 col4
1 1 abc
2 2 def
3 3 xyz
4 4 lmn
5 5 pqr
You can also use select function from dplyr package to subset Data Frame,
library(dplyr)
df %>% select(col2, col4)
# output
col2 col4
1 1 abc
2 2 def
3 3 xyz
4 4 lmn
5 5 pqr
Subset Data Frame based on rows
The Data Frame df contains five rows. Subset df to contain required rows,
Using row indexes,
df[c(1, 3), ]
# output
col1 col2 col3 col4
1 A 1 0.1 abc
3 C 3 0.3 xyz
Using row ranges,
df[c(1:3), ]
# output
col1 col2 col3 col4
1 A 1 0.1 abc
2 B 2 0.2 def
3 C 3 0.3 xyz
Select random rows (in non-sequential order)
df[c(1, 3:5), ]
# output
col1 col2 col3 col4
1 A 1 0.1 abc
3 C 3 0.3 xyz
4 D 4 0.4 lmn
5 E 5 0.5 pqr
Subset Data Frame from Data Frame
Select rows and columns (a subset of DataFrame) using row and column indexes,
df[1:3, 2:3]
# output
col2 col3
1 1 0.1
2 2 0.2
3 3 0.3
Enhance your skills with courses on R
- R Programming
- Data Science: Foundations using R Specialization
- Data Analysis with R Specialization
- Getting Started with Rstudio
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