如何根据一列中的值对数据进行装箱，并汇总R中另一列中的出现次数？

Question

I have a dataframe df and want to bin rows using data from column A, and then for each bin, count the number of times that a value is present in another column B. Here is an example using only 2 columns (although my real example has many columns):

A   B
5.4 
4.6 36_8365
2.4 
3.6 
0.6 
8.9 83_7433
4   
7.6 
4.7 54_3874
1.5 54_8364

I want look in column A, and find all values less than 1, greater than 1 but less than 2, and so on, and for each bin, I want to count the number of times that a value appears in column B. For the table above, this would give the following results:

Class   Number
<1  0
1<=A<2  1
2<=A<3  0
3<=A<4  0
4<=A<5  2
5<=A<6  0
6<=A<7  0
7<=A<8  0
8<=A<9  1
9<=A<10 0

The following is close, but it will sum the values when instead I just want to count them:

with(df, sum(df[A >= 1 & A < 2, "B"]))

I'm not sure what to replace "sum" with to get just counts, instead of a sum. I know I can identify which rows in column B have a value by using

thing <- B==''

or make a table using

thing_table <- table(B=='')

However, I'm not sure how to search through column A, test if the value is between 2 other values, and then count the items in B that meet those criteria. Can anyone point me in the right direction?

Thanks!

Answer 1

First:

newdf<-na.omit(df)

This will shrink the df down to only rows with data in them. Make sure the empty cells are showing up as NAs before attempting.

Second:

Replace sum with length

with(newdf, length(newdf[A>=1 $ A < 2, "B"]))