# How to fill missing values after merging the data frames with another value than NA in R?

To fill missing values after merging the data frames with another value than NA in R, we can follow the below steps −

• First of all, create two data frames.

• Then, merge the data frames by a common column between the two.

• After that, replace the NAs with another value.

## Example

#### Create the first data frame

Let’s create a data frame as shown below −

ID<-1:10
x<-sample(1:100,10)
df1<-data.frame(ID,x)
df1

## Output

On executing, the above script generates the below output(this output will vary on your system due to randomization) −

   ID x
1   1 28
2   2 50
3   3 13
4   4 43
5   5 48
6   6 49
7   7 52
8   8 54
9   9 72
10 10 32

Create the second data frame

Let’s create a data frame as shown below −

ID<-1:15
y<-sample(1:10,15,replace=TRUE)
df2<-data.frame(ID,y)
df2

## Output

On executing, the above script generates the below output(this output will vary on your system due to randomization) −

    ID y
1   1  2
2   2  9
3   3 10
4   4  8
5   5 10
6   6  7
7   7  9
8   8  4
9   9  2
10 10  9
11 11  3
12 12  5
13 13 10
14 14  7
15 15  1

Merge the data frames

Using merge function to merge df1 and df2 by ID column −

ID<-1:10
x<-sample(1:100,10)
df1<-data.frame(ID,x)
ID<-1:15
y<-sample(1:10,15,replace=TRUE)
df2<-data.frame(ID,y)
merge(df1,df2,all=TRUE,by="ID")
DF<-merge(df1,df2,all=TRUE,by="ID")
DF

## Output

    ID x  y
1   1 28  2
2   2 50  9
3   3 13 10
4   4 43  8
5   5 48 10
6   6 49  7
7   7 52  9
8   8 54  4
9   9 72  2
10 10 32  9
11 11 NA  3
12 12 NA  5
13 13 NA 10
14 14 NA  7
15 15 NA  1

Replace NAs with another value

Using is.na function to replace NAs in DF with dot (.) as shown below −

ID<-1:10
x<-sample(1:100,10)
df1<-data.frame(ID,x)
ID<-1:15
y<-sample(1:10,15,replace=TRUE)
df2<-data.frame(ID,y)
merge(df1,df2,all=TRUE,by="ID")
DF<-merge(df1,df2,all=TRUE,by="ID")
DF[is.na(DF)]<-"."
DF

## Output

    ID x  y
1   1 28  2
2   2 50  9
3   3 13 10
4   4 43  8
5   5 48 10
6   6 49  7
7   7 52  9
8   8 54  4
9   9 72  2
10 10 32  9
11 11  .  3
12 12  .  5
13 13  . 10
14 14  .  7
15 15  .  1

Updated on: 16-Nov-2021

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