library(readr)
data1<-read_csv(".../file1")
data2<-read_csv(".../file2")
table2<-table(data1$`_SEGMENT_`,data2$`_SEGMENT_`,data1$Subscribed)
This is the frequency table2 I created with three variables, data1 segment as row, data2 segment as column and third dimension 'Subscribed' with 'yes' and 'no'.
> table2
, , = no
1 2 3 4 5
1 29 674 5189 7207 88
2 3 194 1393 2166 39
3 18 471 2667 5719 77
4 0 1 2 11 0
5 18 420 2798 4715 88
, , = yes
1 2 3 4 5
1 0 33 262 1000 1
2 0 10 65 322 0
3 0 25 190 1206 2
4 0 0 1 3 0
5 0 26 166 943 3
How to create a lift value table of 'yes' based on table2? 5x5 table and each position value = value of 'yes'/(value of 'yes'+value of 'no')
e.g. table_liftvalue[1,2] = 33/(33+674)
> table_liftvalue
1 2 3 4 5
1 . 33/(674+33)
2 .
3 .
4 .
5 .
I appreciate any help. [1]: https://i.sstatic.net/1w6mj.png
Using apply for the sum, then just divide.
table2[,,"yes"]/(apply(table2, 1:2, sum))
# [,1] [,2] [,3] [,4] [,5]
# [1,] 0 0.04667610 0.04806458 0.1218472 0.01123596
# [2,] 0 0.04901961 0.04458162 0.1294212 0.00000000
# [3,] 0 0.05040323 0.06650333 0.1741516 0.02531646
# [4,] NaN 0.00000000 0.33333333 0.2142857 NaN
# [5,] 0 0.05829596 0.05600540 0.1666667 0.03296703
Data:
table2 <- structure(c(29L, 3L, 18L, 0L, 18L, 674L, 194L, 471L, 1L, 420L,
5189L, 1393L, 2667L, 2L, 2798L, 7207L, 2166L, 5719L, 11L, 4715L,
88L, 39L, 77L, 0L, 88L, 0L, 0L, 0L, 0L, 0L, 33L, 10L, 25L, 0L,
26L, 262L, 65L, 190L, 1L, 166L, 1000L, 322L, 1206L, 3L, 943L,
1L, 0L, 2L, 0L, 3L), .Dim = c(5L, 5L, 2L), .Dimnames = list(NULL,
NULL, c("no", "yes")))