如何创建表格以显示R中所有虚拟变量的频率

Question

I am a rookie in R. I want to create a frequency table of all dummy variables and I have a data like this

ID Dummy_2008 Dummy_2009 Dummy_2010 Dummy_2011 Dummy_2012 Dummy_2013
1  1          1          0          0          1          1
2  0          0          1          1          0          1
3  0          0          1          0          0          1
4  0          1          1          0          0          1
5  0          0          0          0          1          0
6  0          0          0          1          0          0

I want to see how total frequency in each variable like this

            0    1   sum
Dummy_2008  5    1   6
Dummy_2009  4    2   6
Dummy_2010  3    3   6
Dummy_2011  4    2   6
Dummy_2012  4    2   6
Dummy_2013  2    4   6

I only know to use table() , but I can only do this one variable a time. I have many time serious dummy variables, and I want to see the trend of them.

Many thanks for the help Terence

Answer 1

result = as.data.frame(t(sapply(dat[,-1], table)))        
result$Sum = rowSums(result)

           0 1 Sum
Dummy_2008 5 1   6
Dummy_2009 4 2   6
Dummy_2010 3 3   6
Dummy_2011 4 2   6
Dummy_2012 4 2   6
Dummy_2013 2 4   6

Explanation:

sapply applies a function to each column of a data frame and returns a matrix. So sapply(dat[,-1], table) returns a matrix with the output of table for each column (except the first column, which we've excluded).

The matrix needs to be transposed so that the column names from the original data frame are the rows and the dummy values are the columns, so we use the t (transpose) function for that.

We want a data frame, not a matrix, so we wrap the whole thing in as.data.frame .

Next, we want another column giving the total number of values, so we use the rowSums function.

Answer 2

Here is another option using mtabulate and addmargins

library(qdapTools)
addmargins(as.matrix(mtabulate(df1[-1])),2)
#           0 1 Sum
#Dummy_2008 5 1   6
#Dummy_2009 4 2   6
#Dummy_2010 3 3   6
#Dummy_2011 4 2   6
#Dummy_2012 4 2   6
#Dummy_2013 2 4   6