I have a data frame which has multiple rows and columns
Data C1 C2 C3
R1 12 33 11
R2 11 2 0
R3 3 3 0
R4 2 3 1
and so on..
How can i drop all the rows from the data frame for which the C3 values are non zero?
The output data should look like
Data C1 C2 C3
R2 11 2 0
R3 3 3 0
I. Using R Basics
df <- data.frame(Data=c("R1","R2","R3","R4"),C1=c(12,11,3,2),C2=c(33,2,3,3),C3=c(11,0,0,1))
df
# Data C1 C2 C3
# 1 R1 12 33 11
# 2 R2 11 2 0
# 3 R3 3 3 0
# 4 R4 2 3 1
df[df$C3 != 0,]
# Data C1 C2 C3
# 1 R1 12 33 11
# 4 R4 2 3 1
II. Using dplyr package's pipe operator %>% and filter() function
library(dplyr)
df %>%
filter(C3 != 0)
# Data C1 C2 C3
# 1 R1 12 33 11
# 2 R4 2 3 1
x[x$C3==0,] should do the trick:
> x
C1 C2 C3
R1 12 33 11
R2 11 2 0
R3 3 3 0
R4 2 3 1
> x[x$C3==0,]
C1 C2 C3
R2 11 2 0
R3 3 3 0
Use filter from dplyr
df <-
df %>%
filter(C3 == 0)
Source: local data frame [2 x 4]
Data C1 C2 C3
<chr> <int> <int> <int>
1 R2 11 2 0
2 R3 3 3 0
to reproduce your output data , however you asked
How can i drop all the rows from the data frame for which the C3 values are non zero?
in which case the code is
df <-
df %>%
filter(C3 != 0)
Source: local data frame [2 x 4]
Data C1 C2 C3
<chr> <int> <int> <int>
1 R1 12 33 11
2 R4 2 3 1
