I'm trying to replace NA values in a column of a dataframe based on strings in R. My data is called flora and looks like this:

I want to replace NA values in the mating system column when the pollination column == "wind" and the cleistogamy column =="cleistogamy not recorded", without affecting existing values in the mating system column.

I've tried multiple approaches but keep coming up with errors. Applying the following code

is.na(flora$msystem) [is.na(flora$pollination)=="wind"& is.na(flora$cleistogamy)=="cleistogamy not recorded"]<- "generally cross"

I get an error saying the replacement has more rows than the data. Nothing seems to change in the data when I try either

flora%>%
  mutate(msystem = if_else(is.na(msystem) & 
                                is.na(pollination)=="wind" &
                                is.na(cleistogamy) == "cleistogamy not recorded", "generally cross", msystem))

or

flora %>% 
  mutate(msystem = case_when(is.na(msystem) & pollination=="wind" & cleistogamy == "cleistogamy not recorded" ~ "generally cross",
                                TRUE ~ msystem))

I'm quite stumped, any advice would be extremely helpful!

CodePudding user response：

Here is one option

library(dplyr)
flora %>% 
  mutate(msystem = case_when(is.na(msystem) & 
              pollination %in% "wind" &
              cleistogamy %in% "cleistogamy not recorded" ~ "generally cross",
                                TRUE ~ msystem))

-output

         species         msystem pollination              cleistogamy
1 Blysmus compressus  generally self        <NA>   entirely cleistogamous
2 Dactylis glomerata generally cross        wind cleistogamy not recorded
3      Daucus carota generally cross        <NA>                     <NA>
4  Agrostis curtisii generally cross        wind cleistogamy not recorded
5  Hornungia petraea  generally self      insect cleistogamy not recorded

data

flora <- structure(list(species = c("Blysmus compressus", "Dactylis glomerata", 
"Daucus carota", "Agrostis curtisii", "Hornungia petraea"), msystem = c("generally self", 
NA, "generally cross", NA, "generally self"), pollination = c(NA, 
"wind", NA, "wind", "insect"), cleistogamy = c("entirely cleistogamous", 
"cleistogamy not recorded", NA, "cleistogamy not recorded", "cleistogamy not recorded"
)), class = "data.frame", row.names = c(NA, -5L))

CodePudding user response：

In general, I think you do not understand what is.na(.) is meant to do. It returns whether the objects in its argument are NA or not. I does not filter or restrict assignment.

A few things:

• Your base code fails because the left side of your assignment is empty:

  is.na(flora$msystem)[is.na(flora$pollination)=="wind"& is.na(flora$cleistogamy)=="cleistogamy not recorded"]
  # logical(0)
  

  We can find out why by breaking it down.

  is.na(flora$msystem)
  # [1] FALSE  TRUE FALSE  TRUE FALSE
  

  The above is fine.

  is.na(flora$pollination)=="wind"
  # [1] FALSE FALSE FALSE FALSE FALSE
  

  The above is a logical error. is.na(.) returns logical, which will never equal the string literal "wind". If you remove is.na, then you have some issues, namely

  flora$pollination == "wind"
  # [1] FALSE  TRUE    NA  TRUE FALSE
  

  One common way around this is to use %in% instead,

  flora$pollination %in% "wind"
  # [1] FALSE  TRUE FALSE  TRUE FALSE
  

  Similarly for your last part, is.na(flora$cleistogomay).

• Further, the base code will not do what you want because the LHS replacement is is.na(flora$mystem), so it will not replace what you want it to. You need to replace the flora$msystem itself.

Perhaps:

flora$msystem <- ifelse(
  is.na(flora$msystem) &
    flora$cleistogamy %in% "cleistogamy not recorded" &
    flora$pollination %in% "wind",
  "generally cross", flora$msystem)
flora
#              species         msystem pollination              cleistogamy
# 1 Blysmus compressus  generally self               entirely cleistogamous
# 2 Dactylis glomerata generally cross        wind cleistogamy not recorded
# 3      Daucus carota generally cross        <NA>                     <NA>
# 4  Agrostis curtisii generally cross        wind cleistogamy not recorded
# 5  Hornungia petraea  generally self      insect cleistogamy not recorded

BTW, both of your dplyr code samples run correctly, but I wonder if you're not reassigning the result back to flora. For instance, contrast this

flora %>%
  mutate(msystem = if_else(is.na(msystem) & cleistogamy == "cleistogamy not recorded" & pollination == "wind", "generally cross", msystem))
#              species         msystem pollination              cleistogamy
# 1 Blysmus compressus  generally self        <NA>   entirely cleistogamous
# 2 Dactylis glomerata generally cross        wind cleistogamy not recorded
# 3      Daucus carota generally cross        <NA>                     <NA>
# 4  Agrostis curtisii generally cross        wind cleistogamy not recorded
# 5  Hornungia petraea  generally self      insect cleistogamy not recorded
flora
#              species         msystem pollination              cleistogamy
# 1 Blysmus compressus  generally self        <NA>   entirely cleistogamous
# 2 Dactylis glomerata            <NA>        wind cleistogamy not recorded
# 3      Daucus carota generally cross        <NA>                     <NA>
# 4  Agrostis curtisii            <NA>        wind cleistogamy not recorded
# 5  Hornungia petraea  generally self      insect cleistogamy not recorded

(unchanged flora contents) with

flora <- flora %>%
  mutate(msystem = if_else(is.na(msystem) & cleistogamy == "cleistogamy not recorded" & pollination == "wind", "generally cross", msystem))
flora
#              species         msystem pollination              cleistogamy
# 1 Blysmus compressus  generally self        <NA>   entirely cleistogamous
# 2 Dactylis glomerata generally cross        wind cleistogamy not recorded
# 3      Daucus carota generally cross        <NA>                     <NA>
# 4  Agrostis curtisii generally cross        wind cleistogamy not recorded
# 5  Hornungia petraea  generally self      insect cleistogamy not recorded