I have a data frame like this
df <- data.frame(v1 = 10:14, v2 = c(NA, 1, NA, 3, 6), v3 = c(1, NA, NA, 9, 4))
v1 v2 v3
1 10 NA 1
2 11 1 NA
3 12 NA NA
4 13 3 9
5 14 6 4
I now want to fill the NAs with the value of the previous column, so it looks like this:
v1 v2 v3
1 10 10 1
2 11 1 1
3 12 12 12
4 13 3 9
5 14 6 4
I know how to do this manually, like this:
df$v2 <- ifelse(is.na(df$v2), df$v1, df$v2)
How can I automate this for a full data frame with many columns?
You can replace values of all or selected columns based on the condition of pandas DataFrame by using DataFrame. loc[ ] property. The loc[] is used to access a group of rows and columns by label(s) or a boolean array. It can access and can also manipulate the values of pandas DataFrame.
You can do this with fill
from tidyr
:
library(dplyr)
library(tidyr)
data.frame(t(df)) %>%
fill(., names(.)) %>%
t()
Result:
v1 v2 v3
X1 10 10 1
X2 11 1 1
X3 12 12 12
X4 13 3 9
X5 14 6 4
Note:
Basically, I transposed df
, filled every column downward, then transposed it back to the original orientation
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