dplyr grouping and using a conditional from multiple columns - r

Question

I have a data frame like this
transactionId user_id total_in_pennies created_at X yearmonth
1 345068 8 9900 2018-09-13 New Customer 2018-09-01
2 346189 8 9900 2018-09-20 Repeat Customer 2018-09-01
3 363500 8 7700 2018-10-11 Repeat Customer 2018-10-01
4 376089 8 7700 2018-10-25 Repeat Customer 2018-10-01
5 198450 11 0 2018-01-18 New Customer 2018-01-01
6 203966 11 0 2018-01-25 Repeat Customer 2018-01-01
it has many more rows, but that little snippet can be used.
I am trying to group using dplyr so I can get a final data frame like this
I use this code
df_RFM11 <- data2 %>% group_by(yearmonth) %>%
summarise(New_Customers=sum(X=="New Customer"), Repeat_Customers=sum(X=="Repeat Customer"), New_Customers_sales=sum(total_in_pennies & X=="New Customers"), Repeat_Customers_sales=sum(total_in_pennies & X=="Repeat Customers"))
and I get this result
> head(df_RFM11)
# A tibble: 6 x 5
yearmonth New_Customers Repeat_Customers New_Customers_sales Repeat_Customers_sales
<date> <int> <int> <int> <int>
1 2018-01-01 4880 2428 0 0
2 2018-02-01 2027 12068 0 0
3 2018-03-01 1902 15296 0 0
4 2018-04-01 1921 13363 0 0
5 2018-05-01 2631 18336 0 0
6 2018-06-01 2339 14492 0 0
and I am able to get the first 2 column I need, the count of new customers and repeat customers, but i get 0's when I try to get the sum of "total_in_pennies" for New Customers and repeat customer
Any help on what am i doing wrong?

Answer 1

You'd need to put them in brackets, like below:
df_RFM11 <- data2 %>%
group_by(yearmonth) %>%
summarise(New_Customers=sum(X=="New Customer"),
Repeat_Customers=sum(X=="Repeat Customer"),
New_Customers_sales=sum(total_in_pennies[X=="New Customer"]),
Repeat_Customers_sales=sum(total_in_pennies[X=="Repeat Customer"])
)