If you wanted to get the subset of a data.frame (DataFrame) Rows & Columns in R, either use the subset() function , filter() from dplyr package or R base square bracket notation df[]. subset() is a generic R function that is used to get the rows and columns (In R terms observations & variables) from the data frame. Also used to get a subset of vectors, and subset of matrices.
In this article, I will explain different ways to subsetting the R DataFrame rows and columns. Alternatively, you can also select rows in R using df[] notation.
1. Create DataFrame
Let’s create a DataFrame in R, run the examples to subset data.frame (DataFrame) rows and columns. and explore the output.
# Create DataFrame
df <- data.frame(
id = c(10,11,12,13,14,15,16,17),
name = c('sai','ram','deepika','sahithi','kumar','scott','Don','Lin'),
gender = c('M','M',NA,'F','M','M','M','F'),
dob = as.Date(c('1990-10-02','1981-3-24','1987-6-14','1985-8-16',
'1995-03-02','1991-6-21','1986-3-24','1990-8-26')),
state = c('CA','NY',NA,NA,'DC','DW','AZ','PH'),
row.names=c('r1','r2','r3','r4','r5','r6','r7','r8')
)
df
Yields below output.
id name gender dob state
r1 10 sai M 1990-10-02 CA
r2 11 ram M 1981-03-24 NY
r3 12 deepika <NA> 1987-06-14 <NA>
r4 13 sahithi F 1985-08-16 <NA>
r5 14 kumar M 1995-03-02 DC
r6 15 scott M 1991-06-21 DW
r7 16 Don M 1986-03-24 AZ
r8 17 Lin F 1990-08-26 PH
2. Subset DataFrame Rows
subset() is used to get the observations and variables from the data frame (DataFrame). Also used to get a subset of vectors, and a subset of matrices.
2.1 Using subset()
This function takes a syntax subset(x, subset, select, drop = FALSE, …) where the first argument is the input object, the second argument is the subset expression and the third is to specify what variables to select.
# subset by row name
subset(df, subset=rownames(df) == 'r1')
# subset row by vector of row names
subset(df, rownames(df) %in% c('r1','r2','r3'))
# subset by condition
subset(df, gender == 'M')
# subset by condition with %in%
subset(df, state %in% c('CA','DC'))
# subset by multiple conditions using |
subset(df, gender == 'M' | state == 'PH')
# subset by multiple conditions using &
subset(df, gender == 'M' & state %in% c('CA','NY'))
2.1 Using df[] Notation
By using bracket notation on R data.frame we can subset rows by name, by index, by column, and by condition e.t.c
# Select Rows by Index
df[3,]
# Select Rows by List of Index Values
df[c(3,4,6),]
# Select Rows by Index Range
df[3:6,]
# Select Rows by column value
df[df$gender == 'M',]
# Select Rows by vector of Values
df[df$state %in% c('CA','AZ','PH'),]
# Select Rows by Checking multiple conditions
df[df$gender == 'M' & df$id > 15,]
2.3 Using filter() Function
Similarly, you can also subset the data.frame by using filter() function from dplyr package. In order to use this, you have to install it first using install.packages('dplyr') and load it using library(dplyr).
# Using dplyr::filter
dplyr::filter(df, state %in% c("CA", "AZ", "PH"))
3. Subset DataFrame Columns
In this section, I will cover how to subset DataFrame (data.frame) columns by using the subset() method, df[] notation, and filter() from dplyr package.
3.1 Using subset() Function
The below examples subset’s DataFrame (data.frame) columns by name and index.
#subset columns by Name
subset(df,gender=='M',select=c('id','name','gender'))
#subset columns by Index
subset(df,gender=='M',select=c(1,2,3))
3.2 Using df[] Notation
By using df[] notation you can also subset the columns. From the following, the example gets the columns with indices 2 and 3 and the second gets the same result but uses the column names.
# Select columns with indices 2 & 3
df[,c(2,3)]
# Selects columns name and gender
df[,c('name','gender')]
4. Complete Example of R Subset Data Frame
# Create DataFrame
df <- data.frame(
id = c(10,11,12,13,14,15,16,17),
name = c('sai','ram','deepika','sahithi','kumar','scott','Don','Lin'),
gender = c('M','M',NA,'F','M','M','M','F'),
dob = as.Date(c('1990-10-02','1981-3-24','1987-6-14','1985-8-16',
'1995-03-02','1991-6-21','1986-3-24','1990-8-26')),
state = c('CA','NY',NA,NA,'DC','DW','AZ','PH'),
row.names=c('r1','r2','r3','r4','r5','r6','r7','r8')
)
df
# subset by row name
subset(df, subset=rownames(df) == 'r1')
# subset row by vector of row names
subset(df, rownames(df) %in% c('r1','r2','r3'))
# subset by condition
subset(df, gender == 'M')
# subset by condition with %in%
subset(df, state %in% c('CA','DC'))
# subset by multiple conditions using |
subset(df, gender == 'M' | state == 'PH')
# subset by multiple conditions using &
subset(df, gender == 'M' & state %in% c('CA','NY'))
# subset Rows by Index
df[3,]
# subset Rows by List of Index Values
df[c(3,4,6),]
# subset Rows by Index Range
df[3:6,]
# subset Rows by column value
df[df$gender == 'M',]
# subset Rows by vector of Values
df[df$state %in% c('CA','AZ','PH'),]
# subset Rows by Checking multiple conditions
df[df$gender == 'M' & df$id > 15,]
# Using dplyr::filter
dplyr::filter(df, state %in% c("CA", "AZ", "PH"))
# Subset columns by Name
subset(df,gender=='M',select=c('id','name','gender'))
# subset columns by Index
subset(df,gender=='M',select=c(1,2,3))
# subset columns with indices 2 & 3
df[,c(2,3)]
# subset columns name and gender
df[,c('name','gender')]
5. Conclusion
In this article, you have learned how to Subset the data frame rows and columns in R by using the subset() function, filter() from dplyr package, and using df[] notation.
Related Articles
- How to Select Rows by Index in R with Examples
- How to Select Rows by Condition in R with Examples
- How to Select Rows by Column Values in R
- R subset() function from dplyr package
- R filter() function from dplyr package
- R select() function from dplyr package
- R mutate() function from dplyr package
- How to select rows by name in R?
- How to subset dataframe by column value in R?
- How to filter dataframe by column value?
