I have a data frame that has unique groups defined by 3 character variables
catvars <- c("DATE", "COUNTRY_FULL_NAME", "TENOR")
The rest of the data frame consists of 20 numeric variables (condensing it to 3 in the sample below)
numvars <- c("X1", "Y1, "Z1")
I am trying to create a new data frame with the mean for each numeric variable calculates by group
For a single variable, I can use ddply from the plyr package:
DFsum <- ddply(DF, catvars, summarize, X1mean = mean(X, na.rm=TRUE))
But I can't figure out how to modify this ddply command to include all numeric variables. Any suggestions? Thank you
I think you're looking for numcolwise
?
ddply(diamonds,.(cut),numcolwise(mean,na.rm = TRUE))
cut carat depth table price x y z
1 Fair 1.0461366 64.04168 59.05379 4358.758 6.246894 6.182652 3.982770
2 Good 0.8491847 62.36588 58.69464 3928.864 5.838785 5.850744 3.639507
3 Very Good 0.8063814 61.81828 57.95615 3981.760 5.740696 5.770026 3.559801
4 Premium 0.8919549 61.26467 58.74610 4584.258 5.973887 5.944879 3.647124
5 Ideal 0.7028370 61.70940 55.95167 3457.542 5.507451 5.520080 3.401448
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