Conditional Cumulative Sum in R

Question

I have a time series data frame and want to compute cumulative returns for stock symbols intra-day for a range of dates. When the symbol and/or date changes the cumulative

Answer 1

Sample data (note: I used lubridate library just to call the dmy function)

library(lubridate) 
df <- data.frame(
  Date = dmy( c( "1/2/2013", "1/2/2013", "1/2/2013", "1/2/2013"
                 , "1/2/2013", "1/2/2013", "1/3/2013", "1/3/2013", "1/3/2013" ) ),
  Symbol = c( "AA", "AA", "AA", "AAPL", "AAPL", "AAPL", "AA", "AA", "AA" ),
  Return = c( NA, 1.19, 0.89, NA, 0.22, 0.21, NA, -1.80, -0.52 )
)

Now, using dplyr, you can group_by your dataframe and create the desired column Cum_Sum:

library(dplyr)
df %>% group_by(Date, Symbol) %>% 
  mutate( Return_aux = ifelse( is.na(Return), 0, Return ), #remove NA
          Cum_Sum = cumsum(Return_aux) )

# A tibble: 9 x 5
# Groups:   Date, Symbol [3]
  Date       Symbol Return Return_aux Cum_Sum
                   
1 2013-02-01 AA      NA          0       0   
2 2013-02-01 AA       1.19       1.19    1.19
3 2013-02-01 AA       0.89       0.89    2.08
4 2013-02-01 AAPL    NA          0       0   
5 2013-02-01 AAPL     0.22       0.22    0.22
6 2013-02-01 AAPL     0.21       0.21    0.43
7 2013-03-01 AA      NA          0       0   
8 2013-03-01 AA      -1.8       -1.8    -1.8 
9 2013-03-01 AA      -0.52      -0.52   -2.32