Home/ Questions/Q 8798503
In Process

The Archive Base Latest Questions

Editorial Team
  • 0
Asked: 2026-06-14T00:06:43+00:00

I have a data.table which contains multiple columns, which is well represented by the

  • 0

I have a data.table which contains multiple columns, which is well represented by the following: 

DT <- data.table(date = as.IDate(rep(c("2012-10-17", "2012-10-18", "2012-10-19"), each=10)), 
                   session = c(1,2,3), price = c(10, 11, 12,13,14), 
                   volume = runif(30, min=10, max=1000))

I would like to extract a multiple column table which shows the volume traded at each price in a particular type of session — with each column representing a date.

At present, i extract this data one date at a time using the following: 

DT[session==1,][date=="2012-10-17", sum(volume), by=price]

and then bind the columns.

Is there a way of obtaining the end product (a table with each column referring to a particular date) without sticking all the single queries together — as i’m currently doing?

thanks

Share

Leave an answer

You must login to add an answer.

Need An Account,

1 Answer

  1. Editorial Team

    Does the following do what you want.

    A combination of reshape2 and data.table

    library(reshape2)

.DT <- DT[,sum(volume),by = list(price,date,session)][, DATE := as.character(date)]
# reshape2 for casting to wide -- it doesn't seem to like IDate columns, hence
# the character DATE co
dcast(.DT, session + price ~ DATE, value.var = 'V1')

    session price 2012-10-17 2012-10-18 2012-10-19
1        1    10   308.9528   592.7259         NA
2        1    11   649.7541         NA   816.3317
3        1    12         NA   502.2700   766.3128
4        1    13   424.8113   163.7651         NA
5        1    14   682.5043         NA   147.1439
6        2    10         NA   755.2650   998.7646
7        2    11   251.3691   695.0153         NA
8        2    12   791.6882         NA   275.4777
9        2    13         NA   111.7700   240.3329
10       2    14   230.6461   817.9438         NA
11       3    10   902.9220         NA   870.3641
12       3    11         NA   719.8441   963.1768
13       3    12   361.8612   563.9518         NA
14       3    13   393.6963         NA   718.7878
15       3    14         NA   871.4986   582.6158

    If you just wanted session 1

    dcast(.DT[session == 1L], session + price ~ DATE)

   session price 2012-10-17 2012-10-18 2012-10-19
1        1    10   308.9528   592.7259         NA
2        1    11   649.7541         NA   816.3317
3        1    12         NA   502.2700   766.3128
4        1    13   424.8113   163.7651         NA
5        1    14   682.5043         NA   147.1439
    • 0