Reputation: 165
I've a dataframe which I want to add a row on the basis of the following conditions. The conditions are when column a
is equal to C
and column b
is equal to 3
or 5
.
Here is my dataframe
df <- data.frame(a = c("A", "B", "C", "D", "C", "A", "C", "E"),
b = c(seq(8)), stringsAsFactors = TRUE)
Whenever the condition is TRUE
I want to add a row below where the condition is met add 3
. I have tried the following
rbind(df, data.frame(a="add", b = "3"))
# a b
# 1 A 1
# 2 B 2
# 3 C 3
# 4 D 4
# 5 C 5
# 6 A 6
# 7 C 7
# 8 E 8
# 9 add 3
This is not the output I want. The output I want is
# a b
# 1 A 1
# 2 B 2
# 3 C 3
# 4 add 3
# 5 D 4
# 6 C 5
# 7 add 3
# 8 A 6
# 9 C 7
# 10 E 8
How can I do that? I am new to R
and thank you for your help.
Upvotes: 3
Views: 267
Reputation: 388982
In base R, we can find out position where a = "c"
and b
is 3 or 5. Repeat those rows in the dataframe and replace them with required values.
pos <- which(df$a == "C" & df$b %in% c(3, 5))
df <- df[sort(c(seq(nrow(df)), pos)), ]
df[seq_along(pos) + pos, ] <- list("add", 3)
row.names(df) <- NULL
df
# a b
#1 A 1
#2 B 2
#3 C 3
#4 add 3
#5 D 4
#6 C 5
#7 add 3
#8 A 6
#9 C 7
#10 E 8
data
df <- data.frame(a = c("A", "B", "C", "D", "C", "A", "C", "E"),
b = c(seq(8)), stringsAsFactors = FALSE)
Upvotes: 2
Reputation: 39154
A solution using the tidyverse
package.
library(tidyverse)
df2 <- df %>%
mutate(Group = lag(cumsum(a == "C" & b %in% c(3, 5)), default = FALSE)) %>%
group_split(Group) %>%
map_dfr(~ .x %>% bind_rows(tibble(a = "add", b = 3))) %>%
slice(-n()) %>%
select(-Group)
df2
# # A tibble: 10 x 2
# a b
# <chr> <dbl>
# 1 A 1
# 2 B 2
# 3 C 3
# 4 add 3
# 5 D 4
# 6 C 5
# 7 add 3
# 8 A 6
# 9 C 7
# 10 E 8
Upvotes: 3
Reputation: 32548
lens = ifelse(df$b %in% c(3, 5) & df$a == "C", 2, 1)
ind = rep(1:NROW(df), lens)
df2 = df[ind,]
df2$a = as.character(df2$a)
df2$a[cumsum(lens)[which(lens == 2)]] = "add"
df2$b[cumsum(lens)[which(lens == 2)]] = 3
df2
# a b
#1 A 1
#2 B 2
#3 C 3
#3.1 add 3
#4 D 4
#5 C 5
#5.1 add 3
#6 A 6
#7 C 7
#8 E 8
Upvotes: 4