检查数据框列是否有空单元格

Question

I am checking if my column (name) have any empty cell but getting error. any solution....??? i am trying in this way.... also how i can disregard if that cell has space, i mean remove space if that cell have then check if t is empty, i just don't want change original name column, while checking i just want to remove spaces or NA and the check if the cells are empty.

df8 <- data.frame(name=c("try,xab","xab,Lan","mhy,mun","vgtu,mmc","dgsy,aaf","kull,nnhu","hula,njam","mund,jiha","htfy,ntha","","sgyu,hytb","vdti,kula","mftyu,huta","","cday,bhsue","ajtu,nudj"),
                  email=c("xab.try@ybcd.com","Lan.xab@ybcd.com","tth.vgu@ybcd.com","mmc.vgtu@ybcd.com","aaf.dgsy@ybcd.com","nnhu.kull@ybcd.com","njam.hula@ybcd.com","jiha.mund@ybcd.com","ntha.htfy@ybcd.com","gydbt.bhr@ybcd.com","hytb.sgyu@ybcd.com","kula.vdti@ybcd.com","huta.mftyu@ybcd.com","ggat.khul@ybcd.com","bhsue.cday@ybcd.com","nudj.ajtu@ybcd.com"))

df8 <- df8 %>% mutate(is_blank_node = which(df8$name == "", arr.ind = TRUE),1 )

Error:

Error: Problem with mutate() input is_blank_node.
x Input is_blank_name can't be recycled to size 182753.
i Input is_blank_name is which(df$Name == "", arr.ind = TRUE).
i Input is_blank_name must be size 182753 or 1, not 0.

expected output

Answer 1

You don't need which at all. In fact, it causes the error here since the result is of length 2 (only the TRUE values are taken into account) and it returns the position of the positive outcomes of your test only. mutate can take the result from name == "" directly. dplyr also knows already that you evaluate the column name within df8 . So you can (and should) omit df$ :

df8 <- data.frame(name=c("try,xab","xab,Lan","mhy,mun","vgtu,mmc","dgsy,aaf","kull,nnhu","hula,njam","mund,jiha","htfy,ntha","","sgyu,hytb","vdti,kula","mftyu,huta","","cday,bhsue","ajtu,nudj"),
                  email=c("xab.try@ybcd.com","Lan.xab@ybcd.com","tth.vgu@ybcd.com","mmc.vgtu@ybcd.com","aaf.dgsy@ybcd.com","nnhu.kull@ybcd.com","njam.hula@ybcd.com","jiha.mund@ybcd.com","ntha.htfy@ybcd.com","gydbt.bhr@ybcd.com","hytb.sgyu@ybcd.com","kula.vdti@ybcd.com","huta.mftyu@ybcd.com","ggat.khul@ybcd.com","bhsue.cday@ybcd.com","nudj.ajtu@ybcd.com"))

library(tidyverse)

df8 %>% 
  mutate(is_blank_node = name == "")
#>          name               email is_blank_node
#> 1     try,xab    xab.try@ybcd.com         FALSE
#> 2     xab,Lan    Lan.xab@ybcd.com         FALSE
#> 3     mhy,mun    tth.vgu@ybcd.com         FALSE
#> 4    vgtu,mmc   mmc.vgtu@ybcd.com         FALSE
#> 5    dgsy,aaf   aaf.dgsy@ybcd.com         FALSE
#> 6   kull,nnhu  nnhu.kull@ybcd.com         FALSE
#> 7   hula,njam  njam.hula@ybcd.com         FALSE
#> 8   mund,jiha  jiha.mund@ybcd.com         FALSE
#> 9   htfy,ntha  ntha.htfy@ybcd.com         FALSE
#> 10             gydbt.bhr@ybcd.com          TRUE
#> 11  sgyu,hytb  hytb.sgyu@ybcd.com         FALSE
#> 12  vdti,kula  kula.vdti@ybcd.com         FALSE
#> 13 mftyu,huta huta.mftyu@ybcd.com         FALSE
#> 14             ggat.khul@ybcd.com          TRUE
#> 15 cday,bhsue bhsue.cday@ybcd.com         FALSE
#> 16  ajtu,nudj  nudj.ajtu@ybcd.com         FALSE

^{Created on 2020-09-17 by the reprex package (v0.3.0)}

update

TRUE and FALSE are basically equivalent to 1 and 0 just in logical instead of integer / numeric type. You can try this with TRUE * 1 which turns the logical into a numeric value. Or use as.integer directly. To get around the problem of cells being filled only with whitespace or NA you can also include extra steps. Since this is getting a bit verbose, we can wrap it in a function:

check_blank <- function(x) {
  as.integer(trimws(ifelse(is.na(x), "", x)) == "")
}

df8 %>% 
  mutate(is_blank_node = check_blank(name))
#>          name               email is_blank_node
#> 1     try,xab    xab.try@ybcd.com             0
#> 2     xab,Lan    Lan.xab@ybcd.com             0
#> 3     mhy,mun    tth.vgu@ybcd.com             0
#> 4    vgtu,mmc   mmc.vgtu@ybcd.com             0
#> 5    dgsy,aaf   aaf.dgsy@ybcd.com             0
#> 6   kull,nnhu  nnhu.kull@ybcd.com             0
#> 7   hula,njam  njam.hula@ybcd.com             0
#> 8   mund,jiha  jiha.mund@ybcd.com             0
#> 9   htfy,ntha  ntha.htfy@ybcd.com             0
#> 10             gydbt.bhr@ybcd.com             1
#> 11  sgyu,hytb  hytb.sgyu@ybcd.com             0
#> 12  vdti,kula  kula.vdti@ybcd.com             0
#> 13 mftyu,huta huta.mftyu@ybcd.com             0
#> 14             ggat.khul@ybcd.com             1
#> 15 cday,bhsue bhsue.cday@ybcd.com             0
#> 16  ajtu,nudj  nudj.ajtu@ybcd.com             0

^{Created on 2020-09-17 by the reprex package (v0.3.0)}

Answer 2

Maybe you can try nchar like below

df8 %>%
  mutate(is_blank_node = +(nchar(name)==0))

or nzchar

df8 %>%
  mutate(is_blank_node = +!nzchar(name))

which gives

> df8 %>%
+   mutate(is_blank_node = +(nchar(name)==0))
         name               email is_blank_node
1     try,xab    xab.try@ybcd.com             0
2     xab,Lan    Lan.xab@ybcd.com             0
3     mhy,mun    tth.vgu@ybcd.com             0
4    vgtu,mmc   mmc.vgtu@ybcd.com             0
5    dgsy,aaf   aaf.dgsy@ybcd.com             0
6   kull,nnhu  nnhu.kull@ybcd.com             0
7   hula,njam  njam.hula@ybcd.com             0
8   mund,jiha  jiha.mund@ybcd.com             0
9   htfy,ntha  ntha.htfy@ybcd.com             0
10             gydbt.bhr@ybcd.com             1
11  sgyu,hytb  hytb.sgyu@ybcd.com             0
12  vdti,kula  kula.vdti@ybcd.com             0
13 mftyu,huta huta.mftyu@ybcd.com             0
14             ggat.khul@ybcd.com             1
15 cday,bhsue bhsue.cday@ybcd.com             0
16  ajtu,nudj  nudj.ajtu@ybcd.com             0

Answer 3

Base R solution, checking if any empty strings in all vectors:

data.frame(+(t(apply(df8, 1, `==`, ""))))

Base R, with results column-bind to the original data.frame:

cbind(df8, setNames(data.frame(+(t(apply(df8, 1, `==`, "")))), 
         paste("empty", names(df8), sep = "_")))

Answer 4

This will mutate said column with your desired values (1 or 0)

df8 <- df8 %>% mutate(is_blank_node = ifelse(name == "", 1, 0))

Update: added line that removes any whitespace from the column, then will check if the cell is empty...

df8 <- df8 %>% 
  mutate(name = trimws(name, which = "both")) %>%
  mutate(is_blank_node = ifelse(name == "", 1, 0))

Update 2: This will give a '1' to any cell detected as blank or having only spaces (no matter amount of spaces), and give a '0' to anything else. This does not change the contents of the original column.

library(tidyverse)

df8 <- df8 %>% mutate(is_blank_node = ifelse(name == "" | str_detect(name, '^\\s*$'), 1, 0))