T4 <- table(bank$Term_deposit, bank$housing_loan)
%>% prop.table(margin = 2) *100

T4

           no       yes
  no  83.418772 92.217126 <br/>
  yes 16.581228  7.782874

kable(T4, caption = "%agewise comparison for marital status")

|    |       no|       yes|<br/>
|:---|--------:|---------:|<br/>
|no  | 83.41877| 92.217126|<br/>
|yes | 16.58123|  7.782874|<br/>

|    |       no|       yes|<br/>
|:---|--------:|---------:|<br/>
CAT1 | 83.41877| 92.217126|<br/>
|CAT2| 16.58123|  7.782874|

|    |     cat1|      cat2|<br/>
|:---|--------:|---------:|<br/>
CAT1 | 83.41877| 92.217126|<br/>
|CAT2| 16.58123|  7.782874|<br/>

library(pandoc)

colnames(T4) <- c("CAT1", "CAT2")
rownames(T4) <- c("no", "yes")
pandoc.table(T4)

-------------------------
 &nbsp;    CAT1    CAT2
-------- -------- -------
 **y**    13473    77311

 **n**    226221     0
-------------------------

colnames(T4) <- c("deposit: no", "deposit: yes")
rownames(T4) <- c("loan: no", "loan: yes")
pandoc.table(T4)

--------------------------------------------
    &nbsp;       deposit: no   deposit: yes
--------------- ------------- --------------
 **loan: no**       13473         77311

 **loan: yes**     226221           0
--------------------------------------------

library(expss)

df <- apply_labels(bank,
                   Term_deposit= "Term deposit",
                   housing_loan= "Housing loan")

cro_cpct(bank$Term_deposit, bank$housing_loan)

|              |              | Housing loan |     |
 |              |              |            0 |   1 |
 | ------------ | ------------ | ------------ | --- |
 | Term deposit |            0 |         39.4 | 100 |
 |              |            1 |         60.6 |     |
 |              | #Total cases |         66.0 |  34 |