The data.table R Package Cheat Sheet

data.table

data.table is an R package that provides a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use, convenience and programming speed. 

Load the Package:

library(data.table)

Creating a data.table

> set.seed(45L) #Create a data.table and call it DT
> DT <- data.table(V1=c(1L,2L), V2=LETTERS[1:3], V3=round(rnorm(4),4), V4=1:12)

Subsetting Rows Using i

> DT[3:5,] #Select 3rd to 5th row
> DT[3:5] #Select 3rd to 5th row
> DT[V2=="A"] #Select all rows that have value A in column V2
> DT[V2 %in% c("A","C")] #Select all rows that have value A or C in column V2

Manipulating on columns in j

> DT[,V2] Return V2 as a vector
 [1] “A” “B” “C” “A” “B” “C” ...
> DT[,.(V2,V3)] #Return V2 and V3 as a data.table
> DT[,sum(V1)] #Return the sum of all elements of V1 in a vector
 [1] 18 

#Return the sum of all elements of V1 and the std. dev. of V3 in a data.table
> DT[,.(sum(V1),sd(V3))] 
    V1 V2 
 1: 18 0.4546055

#The same as the above, with new names
> DT[,.(Aggregate=sum(V1), Sd.V3=sd(V3))]
    Aggregate Sd.V3
    1: 18        0.4546055

# Select column V2 and compute std. dev. of V3, which returns a single value & gets recycled
> DT[,.(V1,Sd.V3=sd(V3))] 
#Print column V2 and plot V3
> DT[,.(print(V2), plot(V3), NULL)]

Chaining

#Calculate sum of V4, grouped by V1
> DT <- DT[,.(V4.Sum=sum(V4)), by=V1]
    V1   V4.Sum
 1: 1    36
 2: 2    42

#Select that group of which the sum is >40
> DT[V4.Sum>40] 

#Select that group of which the sum is >40 (chaining)
> DT[,.(V4.Sum=sum(V4)), by=V1][V4.Sum>40] 
    V1   V4.Sum
 1: 2    42

#Calculate sum of V4, grouped by ordered on V1
> DT[,.(V4.Sum=sum(V4)), by=V1][order(-V1)] 
    V1   V4.Sum
 1: 2    42
 2: 1    36

Doing j by Group

#Calculate sum of V4 for every group in V1 Sum
> DT[,.(V4.Sum=sum(V4)),by=V1] 
    V1 V4.
 1: 1 36
 2: 2 42

#Calculate sum of V4 for every group in V1 and V2 
> DT[,.(V4.Sum=sum(V4)), by=.(V1,V2)] 


#Calculate sum of V4 for every group in sign(V1-1)
> DT[,.(V4.Sum=sum(V4)), by=sign(V1-1)]  
   sign V4.Sum
1: 0    36
2: 1    42

#The same as the above, with new name for the variable you’re grouping by
> DT[,.(V4.Sum=sum(V4)), by=.(V1.01=sign(V1-1))] 

#Calculate sum of V4 for every group in V1 after subsetting on the first 5 rows
> DT[1:5,.(V4.Sum=sum(V4)), by=V1] 
> DT[,.N,by=V1] #Count number of rows for every group in V1

Adding/Updating Columns by Reference in j using :=

> DT[,V1:=round(exp(V1),2)] #V1 is updated by what is after :=

> DT Return the result by calling DT
    V1      V2     V3          V4
 1: 2.72    A     -0.1107      1
 2: 7.39    B     -0.1427      2
 3: 2.72    C     -1.8893      3
 4: 7.39    A     -0.3571      4
 ...

#Columns V1 & V2 are updated by what is after :=
> DT[,c("V1","V2"):=list(round(exp(V1),2), LETTERS[4:6])] 

#Alternative to the above one. With [], you print the result to the screen
> DT[,':='(V1=round(exp(V1),2), V2=LETTERS[4:6])][] 

    V1       V2     V3         V4
 1: 15.18    D     -0.1107     1
 2: 1619.71  E     -0.1427     2
 3: 15.18    F     -1.8893     3
 4: 1619.71  D     -0.3571     4

# Remove V1
> DT[,V1:=NULL] 

#Remove columns V1 and V2
> DT[,c("V1","V2"):=NULL] 

#Delete the column with column name Cols.chosen
> Cols.chosen=c("A","B")
> DT[,Cols.Chosen:=NULL] 

#Delete the columns specified in the variable Cols.chosen
> DT[,(Cols.Chosen):=NULL] 

set()-Family

set()

Syntax: for (i in from:to) set(DT, row, column, new value)

> rows <- list(3:4,5:6)
> cols <- 1:2

#Sequence along the values of rows, and for the values of cols,  set the values of those elements equal to NA (invisible)
> for(i in seq_along(rows))
 {set(DT, 
 i=rows[[i]], 
 j=cols[i],
 value=NA)}

setnames()

Syntax: setnames(DT,"old","new")[]

> setnames(DT,"V2","Rating") #Set name of V2 to Rating (invisible)
> setnames(DT, #Change 2 column names (invisible)
 c("V2","V3"),
 c("V2.rating","V3.DC"))

setcolorder()

Syntax: setcolorder(DT,"neworder")

#Change column ordering to contents of the specified vector (invisible)
> setcolorder(DT, c("V2","V1","V4","V3")) 

Advanced Data Table Operations

> DT[.N-1] #Return the penultimate row of the DT
> DT[,.N] #Return the number of rows
> DT[,.(V2,V3)] #Return V2 and V3 as a data.table
> DT[,list(V2,V3)] #Return V2 and V3 as a data.table

#Return the result of j, grouped by all possible combinations of groups specified in by
> DT[,mean(V3),by=.(V1,V2)] 
    V1    V2     V1 
 1: 1     A      0.4053
 2: 1     B      0.4053
 3: 1     C      0.4053
 4: 2     A     -0.6443
 5: 2     B     -0.6443
 6: 2     C     -0.6443

.SD & SDCols

> DT[,print(.SD),by=V2] #Look at what .SD contains
> DT[,.SD[c(1,.N)],by=V2] #Select the first and last row grouped by V2
> DT[,lapply(.SD,sum),by=V2] #Calculate sum of columns in .SD grouped by V2

#Calculate sum of V3 and V4 in .SD grouped by V2
> DT[,lapply(.SD,sum),by=V2, .SDcols=c("V3","V4")]
    V2    V3        V4
 1: A     -0.478    22
 2: B     -0.478    26
 3: C     -0.478    30

#Calculate sum of V3 and V4 in .SD grouped by V2
> DT[,lapply(.SD,sum),by=V2, .SDcols=paste0("V",3:4)] 

Indexing and Keys

> setkey(DT,V2) #A key is set on V2; output is returned invisibly
> DT["A"] #Return all rows where the key column (set to V2) has the value A
    V1     V2     V3          V4 
 1: 1      A      -0.2392     1
 2: 2      A      -1.6148     4
 3: 1      A      1.0498      7
 4: 2      A      0.3262      10
> DT[c("A","C")] #Return all rows where the key column (V2) has value A or C
> DT["A",mult="first"] #Return first row of all rows that match value A in key column V2
> DT["A",mult="last"] #Return last row of all rows that match value A in key column V2

> DT[c("A","D")] #Return all rows where key column V2 has value A or D
    V1   V2    V3         V4
 1: 1    A    -0.2392     1
 2: 2    A    -1.6148     4
 3: 1    A     1.0498     7
 4: 2    A     0.3262     10
 5: NA   D     NA         NA

> DT[c("A","D"),nomatch=0] #Return all rows where key column V2 has value A or D
    V1     V2    V3           V4
 1: 1      A     -0.2392      1
 2: 2      A     -1.6148      4
 3: 1      A      1.0498      7
 4: 2      A      0.3262      10

#Return total sum of V4, for rows of key column V2 that have values A or C
> DT[c("A","C"),sum(V4)] 

#Return sum of column V4 for rows of V2 that have value A, sum(V4), and another sum for rows of V2 that have value C
> DT[c("A","C"), by=.EACHI]
    V2     V1
 1: A      22
 2: C      30

#Sort by V1 and then by V2 within each group of V1 (invisible)
> setkey(DT,V1,V2) 

#Select rows that have value 2 for the first key (V1) &  the value C for the second key (V2)
> DT[.(2,"C")]  
    V1    V2    V3         V4 
 1: 2     C     0.3262     6
 2: 2     C     -1.6148    12

# Select rows that have value 2 for the first key (V1) & within those rows the value A or C for the second key (V2)
> DT[.(2,c("A","C"))] 
    V1   V2    V3          V4 
 1: 2    A     -1.6148     4
 2: 2    A     0.3262      10
 3: 2    C     0.3262      6
 4: 2    C     -1.6148     12