I'm trying to match 4 variables pairwise and add a column with the lookup value. In base, I would do merge(df1,df2, by.x=c("lsr","ppr"),by.y=c("li","pro"))
, where df1
has 9 cols and df2
(2 being lsr
and pro
) df2
has only 3, li
, pro
, and the "value" I'm interested in, alpha
.
This works fine, but as I'm beginning to be a huge fan of data.table
, I would like to do this in the data.table
way - and because I have some millions of rows - so base merge is slow (I saw, that the by.x
, and by.y
feature is pending for data.table
, but maybe there is a workaround). See some sample data below:
df2:
alpha li pro
1: 0.5000000 0.01666667 0.01666667
2: 0.3295455 0.03333333 0.01666667
3: 0.2435897 0.05000000 0.01666667
4: 0.1917808 0.06666667 0.01666667
5: 0.1571429 0.08333333 0.01666667
df1:
demand rtime mcv mck ppr mlv mlk lsr
1: 0.3 1 357.57700 0.099326944 0.01666667 558.27267 0.155075741 0.01666667
2: 0.3 10 548.75433 0.152431759 0.01666667 614.30667 0.170640741 0.03333333
3: 0.3 11 314.55767 0.087377130 0.01666667 636.48100 0.176800278 0.03333333
4: 0.3 2 312.15033 0.086708426 0.01666667 677.48100 0.188189167 0.06666667
5: 0.3 3 454.47867 0.126244074 0.01666667 608.92067 0.169144630 0.01666667
---
6899196: 0.6 5 537.92673 0.149424093 1.00000000 537.92673 0.149424093 1.00000000
6899197: 0.6 6 277.34732 0.077040923 1.00000000 277.34732 0.077040923 1.00000000
6899198: 0.6 7 73.31484 0.020365235 1.00000000 73.31484 0.020365235 1.00000000
6899199: 0.6 8 32.04197 0.008900546 1.00000000 32.04197 0.008900546 1.00000000
6899200: 0.6 9 14.59008 0.004052799 1.00000000 14.59008 0.004052799 1.00000000
Last, maybe of interest is, that in df2
I have unique rows, and in df1
, I have lots of duplicates in respect to lsr
and ppr
. I also tried to set two keys and join them the data.table
way, and adding a new column with alpha
. But without success.
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