How to Replace Empty String with Na in R Dataframe

How to replace empty string with NA in R dataframe?

I'm not sure why df[df==""]<-NA would not have worked for OP. Let's take a sample data.frame and investigate options.

Option#1: Base-R

df[df==""]<-NA

df
#    One  Two Three Four
# 1    A    A  <NA>  AAA
# 2 <NA>    B    BA <NA>
# 3    C <NA>    CC  CCC

Option#2: dplyr::mutate_all and na_if. Or mutate_if if the data frame has multiple types of columns

library(dplyr)

mutate_all(df, list(~na_if(.,"")))

OR

#if data frame other types of character Then
df %>% mutate_if(is.character, list(~na_if(.,""))) 

#    One  Two Three Four
# 1    A    A  <NA>  AAA
# 2 <NA>    B    BA <NA>
# 3    C <NA>    CC  CCC

Toy Data:

df <- data.frame(One=c("A","","C"), 
                 Two=c("A","B",""), 
                 Three=c("","BA","CC"), 
                 Four=c("AAA","","CCC"), 
                 stringsAsFactors = FALSE)

df
#   One Two Three Four
# 1   A   A        AAA
# 2       B    BA     
# 3   C        CC  CCC

How to replace empty strings in a dataframe with NA (missing value) not NA string

By specifying just NA, according to ?NA -"NA is a logical constant of length 1 which contains a missing value."

The class can be checked

class(NA)
#[1] "logical"
class(NA_character_) 
#[1] "character"

and both of them is identified by standard functions such as is.na

is.na(NA)
#[1] TRUE
is.na(NA_character_)
#[1] TRUE

The if_else is type sensitive, so instead of specifying as NA which returns a logical output, it can specified as either NA_real_, NA_integer_, NA_character_ depending on the type of the 'boat' column. Assuming that the 'boat' is character class, we may need NA_character_

titanic %>% 
       mutate(boat = if_else(boat=="", NA_character_ ,boat))

Change the Blank Cells to NA

I'm assuming you are talking about row 5 column "sex." It could be the case that in the data2.csv file, the cell contains a space and hence is not considered empty by R.

Also, I noticed that in row 5 columns "axles" and "door", the original values read from data2.csv are string "NA". You probably want to treat those as na.strings as well. To do this,

dat2 <- read.csv("data2.csv", header=T, na.strings=c("","NA"))

EDIT:

I downloaded your data2.csv. Yes, there is a space in row 5 column "sex". So you want

na.strings=c(""," ","NA")

Replace all string instances of NULL with actual NULL or NA in a data frame

Just do this:

exampledf[exampledf=="NULL"] <- NA

or with dplyr

exampledf <- exampledf %>% replace(exampledf == "NULL", NA)

Replace missing values (NA) with blank (empty string)

Another alternative:

df <- sapply(df, as.character) # since your values are `factor`
df[is.na(df)] <- 0

If you want blanks instead of zeroes

> df <- sapply(df, as.character)
> df[is.na(df)] <- " "
> df
     class    Year1 Year2 Year3 Year4 Year5
[1,] "classA" "A"   "A"   "A"   "A"   "A"  
[2,] " "      " "   " "   " "   " "   " "  
[3,] "classB" "B"   "B"   "B"   "B"   "B"  

If you want a data.frame, then just use as.data.drame

> as.data.frame(df)
   class Year1 Year2 Year3 Year4 Year5
1 classA     A     A     A     A     A
2                                     
3 classB     B     B     B     B     B

How to replace blank strings with NA?

To show that the code works:

data <- data.frame( col1= c("", letters[1:4]), col2=c(letters[1:4], ""))
 is.na(data) <- data==''
 data
 #  col1 col2
 #1 <NA>    a
 #2   a    b
 #3    b    c
 #4    c    d
 #5    d <NA>

Suppose, if you have '' along with spaces ' ', this won't work

 data <- data.frame( col1= c("", letters[1:4]), col2=c(letters[1:4], " "))
 data1 <- data
 is.na(data) <- data==''
  data
  col1 col2
 #1 <NA>    a
 #2    a    b
 #3    b    c
 #4    c    d
 #5    d     

In such cases, you could use str_trim

  library(stringr)
  data1[] <- lapply(data1, str_trim)
  is.na(data1) <- data1==''
  data1
  #  col1 col2
  #1 <NA>    a
  #2    a    b
  #3    b    c
  #4    c    d
  #5    d <NA>

Replace blank with NA in R

What type of variable are we talking about? Numeric? Character?
A better formulated question makes it easier to give a better answer.

This could help:

DT[DT == ""] <- NA

Do not try so hard. R should be fun!

R mutate & replace string with empty pattern or empty string

Try replacing the blank values with NA :

library(dplyr)
library(stringr)

temp %>%
  mutate(to_remove = na_if(to_remove, ''),
         removed = str_remove(entry,to_remove))

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