How to find the row-wise frequency of zeros in an R data frame?
In data analysis, we need to be very cautious about repeated values because they might be inputted purposely to create bias in the data and this value could be a zero as well. It happens in situations when we have missing data and the data collector replaces missing values with zeros which is a wrong practice. To find the row-wise frequency of zeros in an R data frame, we can use rowSums function for zero values by using the syntax −
rowSums(“data_frame_name”==0)
Consider the below data frame −
Example
Live Demo
set.seed(189)
x1<-sample(0:1,20,replace=TRUE)
x2<-sample(0:5,20,replace=TRUE)
x3<-sample(0:2,20,replace=TRUE)
x4<-sample(0:1,20,replace=TRUE)
x5<-sample(0:5,20,replace=TRUE)
x6<-sample(0:10,20,replace=TRUE)
df1<-data.frame(x1,x2,x3,x4,x5,x6) df1
Output
x1 x2 x3 x4 x5 x6
1 1 5 2 1 3 1
2 1 3 0 0 5 2
3 1 2 2 1 2 5
4 1 4 0 0 0 7
5 0 0 2 0 5 0
6 0 5 1 1 2 5
7 0 5 1 1 1 6
8 0 4 1 0 3 1
9 0 4 1 1 3 4
10 0 1 2 0 4 5
11 1 1 2 0 4 0
12 1 2 0 0 5 1
13 1 3 0 0 1 5
14 1 0 0 0 5 1
15 0 3 0 1 5 10
16 0 3 2 1 3 2
17 1 3 0 1 1 7
18 0 3 1 1 2 9
19 1 3 2 0 3 5
20 1 4 0 1 2 1
Counting number of zeros in each row −
Example
df1$Zeros<-rowSums(df1==0)
df1
Output
x1 x2 x3 x4 x5 x6 Zeros
1 0 1 1 0 4 3 2
2 0 4 2 1 4 10 1
3 0 3 2 0 0 3 3
4 0 5 0 0 4 4 3
5 1 1 1 0 3 6 1
6 1 2 1 1 4 5 0
7 1 0 2 0 0 4 3
8 1 0 0 1 3 2 2
9 0 2 0 0 5 1 3
10 0 4 1 1 4 2 1
11 0 3 0 0 1 3 3
12 0 0 0 0 1 5 4
13 1 2 0 1 5 8 1
14 1 1 2 1 1 10 0
15 1 3 0 1 4 6 1
16 1 5 2 0 0 8 2
17 0 1 2 0 0 4 3
18 0 5 2 1 3 1 1
19 1 2 2 0 0 2 2
20 1 3 2 1 3 4 0
Let’s have a look at another example −
Example
Live Demo
y1<-sample(0:2,20,replace=TRUE)
y2<-sample(0:1,20,replace=TRUE)
y3<-sample(0:5,20,replace=TRUE)
y4<-sample(0:4,20,replace=TRUE)
y5<-sample(0:1,20,replace=TRUE)
y6<-sample(0:5,20,replace=TRUE)
y7<-sample(0:10,20,replace=TRUE)
df2<-data.frame(y1,y2,y3,y4,y5,y6)
df2
Output
y1 y2 y3 y4 y5 y6
1 2 1 1 1 0 1
2 0 1 3 1 0 3
3 0 1 5 0 1 1
4 2 1 5 2 1 4
5 0 0 5 0 0 0
6 0 0 1 0 1 4
7 1 0 0 4 1 2
8 0 1 3 1 0 1
9 1 0 4 2 0 1
10 0 0 2 3 0 5
11 2 1 3 2 0 5
12 1 1 5 4 0 2
13 2 0 2 1 0 2
14 2 0 2 4 1 0
15 0 1 3 3 0 1
16 0 1 4 0 1 0
17 1 0 5 2 1 4
18 1 1 3 1 1 0
19 1 1 4 4 1 2
20 2 0 1 1 0 3
Counting number of zeros in each row −
Example
df2$No_of_Zeros <-rowSums(df2==0) df2
Output
y1 y2 y3 y4 y5 y6 No_of_Zeros
1 1 0 2 0 1 5 2
2 1 1 0 3 1 2 1
3 1 1 3 4 1 5 0
4 0 1 0 1 0 0 4
5 1 0 2 1 1 2 1
6 1 1 0 4 1 0 2
7 2 1 0 2 0 3 2
8 1 1 3 2 0 1 1
9 2 0 2 0 0 4 3
10 2 1 1 2 0 5 1
11 0 0 1 4 1 3 2
12 2 1 4 3 0 1 1
13 1 1 3 3 0 1 1
14 1 0 3 2 0 0 3
15 0 1 1 0 0 2 3
16 1 0 5 0 1 5 2
17 0 1 0 3 1 5 2
18 2 1 0 3 1 0 2
19 2 0 0 0 0 5 4
20 1 1 5 4 1 4 0
Published on 16-Oct-2020 15:11:35
Data Structure
Networking
RDBMS
Operating System
Java
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP