To subset with multiple conditions in R, you can use either df[] notation, subset() function from r base package, filter() from dplyr package.
In this article, I will explain different ways to subset the R DataFrame by multiple conditions.
1. Create DataFrame
Let’s create an R DataFrame, run these examples and explore the output. If you already have data in CSV you can easily import CSV files to R DataFrame. Also, refer to Import Excel File into R.
# 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 Rows by Multiple Conditions
The subset() is a R base function that is used to get the observations and variables from the data frame (DataFrame) by submitting with multiple conditions. Also used to get a subset of vectors, and a subset of matrices.
This subset() 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 multiple conditions using |
subset(df, gender == 'M' | state == 'PH')
# subset by multiple conditions using &
subset(df, gender == 'M' & state %in% c('CA','NY'))
Yields below output.
3. Using df[] Notation
By using bracket notation df[] on R data.frame we can also get data frame by multiple conditions
# Select Rows by Checking multiple conditions
df[df$gender == 'M' | df$state == 'PH',]
df[df$gender == 'M' & df$state %in% c('CA','NY'),]
Yields the same output as above.
4. Using filter() Function
Similarly, you can also subset the data.frame by multiple conditions 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).
library(dplyr)
# Using dplyr::filter
df %>% filter(gender == 'M' | state == 'PH')
df %>% filter(gender == 'M' & state %in% c('CA','NY') )
Yields the same output as above.
5. Complete Example
# 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 multiple conditions using |
subset(df, gender == 'M' | state == 'PH')
# subset by multiple conditions using &
subset(df, gender == 'M' & state %in% c('CA','NY'))
# Select Rows by Checking multiple conditions
df[df$gender == 'M' | df$state == 'PH',]
df[df$gender == 'M' & df$state %in% c('CA','NY'),]
library(dplyr)
# Using dplyr::filter
df %>% filter(gender == 'M' | state == 'PH')
df %>% filter(gender == 'M' & state %in% c('CA','NY') )
5. Conclusion
In this article, you have learned how to Subset the data frame by multiple conditions 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?
