Combining rows based on a column

Question

    structure(list(UserID = c(42L, 42L, 42L, 95L, 95L, 95L, 95L, 
95L), TotalSpend_A = c(NA, NA, NA, NA, 177.12, NA, NA, NA), 
    TotalSpend_B = c(NA, 40.78, NA, NA         


        

Answer 1

With dplyr:

library(dplyr)

df %>% 
  group_by(UserID) %>% 
  summarise_all(funs(sum(., na.rm = TRUE)))

# A tibble: 2 x 6
  UserID TotalSpend_A TotalSpend_B TotalSpend_C TotalSpend_D TotalSpend_E
   <int>        <dbl>        <dbl>        <dbl>        <dbl>        <dbl>
1     42         0.00        40.78         6.74            0          0.0
2     95       177.12        62.87        96.91            0          1.1

Base R:

aggregate(. ~ UserID, df, sum, na.rm = TRUE, na.action = "na.pass")

  UserID TotalSpend_A TotalSpend_B TotalSpend_C TotalSpend_D TotalSpend_E
1     42         0.00        40.78         6.74            0          0.0
2     95       177.12        62.87        96.91            0          1.1

And data.table:

DT <- data.table::setDT(df)
DT[, lapply(.SD, mean, na.rm = TRUE), by = UserID]

   UserID TotalSpend_A TotalSpend_B TotalSpend_C TotalSpend_D TotalSpend_E
1:     42          NaN        40.78         6.74          NaN          NaN
2:     95       177.12        62.87        96.91          NaN          1.1