# [R] How to create a new data.frame based on calculation of subsets of an existing data.frame

Ioannou, Ioanna |o@nn@@|o@nnou @end|ng |rom uc|@@c@uk
Fri Dec 20 11:01:58 CET 2019

```Hello Jim,

Thank you every so  much it ws very helful. In fact what I want to calculate is the following. My very last question is if I want to save the outcome VC, IM.type and Taxonomy in a new data.frame how can I do it?

# names of the variables used in the calculations
calc_vars<-paste("Prob.of.exceedance",1:4,sep="_")
# get the rows for the four damage states
DS1_rows <-D\$Damage.state == "DS1"
DS2_rows <-D\$Damage.state == "DS2"
DS3_rows <-D\$Damage.state == "DS3"
DS4_rows <-D\$Damage.state == "DS4"
# step through all possible values of IM.type and Taxonomy
for(IM in unique(D\$IM.type)) {  for(Tax in unique(D\$Taxonomy)) {
# get a logical vector of the rows to be used in this calculation
calc_rows <- D\$IM.type == IM & D\$Taxonomy == Tax
cat(IM,Tax,calc_rows,"\n")
# check that there are any such rows in the data frame
if(sum(calc_rows)) {
# if so, fill in the four values for these rows
VC <- 0.0 * (1- D[calc_rows & DS1_rows,calc_vars]) +
0.02* (D[calc_rows & DS1_rows,calc_vars] -
D[calc_rows & DS2_rows,calc_vars]) +
0.10* (D[calc_rows & DS2_rows,calc_vars] -
D[calc_rows & DS3_rows,calc_vars]) +
0.43 * (D[calc_rows & DS3_rows,calc_vars] -
D[calc_rows & DS4_rows,calc_vars]) +
1.0*   D[calc_rows & DS4_rows,calc_vars]

}
}
}

-----Original Message-----
From: Jim Lemon [mailto:drjimlemon using gmail.com]
Sent: Thursday, December 19, 2019 2:05 AM
To: Ioannou, Ioanna <ioanna.ioannou using ucl.ac.uk>; r-help mailing list <r-help using r-project.org>
Subject: Re: [R] How to create a new data.frame based on calculation of subsets of an existing data.frame

Hi Ioanna,
I looked at the problem this morning and tried to work out what you wanted. With a problem like this, it is often easy when you have someone point to the data and say "I want this added to that and this multiplied by that". I have probably made the wrong guesses, but I hope that you can correct my guesses and I can get the calculations correct for you. For example, I have assumed that you want the sum of the IM_* values for each set of damage states as the values for VC_1,
VC_2 etc.

D<-data.frame(Ref.No = c(1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629),  Region = rep(c('South America'), times = 8),  IM.type = c('PGA', 'PGA', 'PGA', 'PGA', 'Sa', 'Sa', 'Sa', 'Sa'),  Damage.state = c('DS1', 'DS2', 'DS3', 'DS4','DS1', 'DS2', 'DS3', 'DS4'),  Taxonomy = c('ER+ETR_H1','ER+ETR_H1','ER+ETR_H1','ER+ETR_H1','ER+ETR_H2',
'ER+ETR_H2','ER+ETR_H2','ER+ETR_H2'),
IM_1 = c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00),
IM_2 = c(0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 0.08, 0.08),
IM_3 = c(0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16, 0.16),
IM_4 = c(0.24, 0.24, 0.24, 0.24, 0.24, 0.24, 0.24, 0.24),
Prob.of.exceedance_1 = c(0,0,0,0,0,0,0,0),
Prob.of.exceedance_2 = c(0,0,0,0,0,0,0,0),
Prob.of.exceedance_3 =
c(0.26,0.001,0.00019,0.000000573,0.04,0.00017,0.000215,0.000472),
Prob.of.exceedance_4 =
c(0.72,0.03,0.008,0.000061,0.475,0.0007,0.00435,0.000405),
stringsAsFactors=FALSE)
# assume the above has been read in
# add the four columns to the data frame filled with NAs D\$VC_1<-D\$VC_2<-D\$VC_3<-D\$VC_4<-NA
# names of the variables used in the calculations
calc_vars<-paste("Prob.of.exceedance",1:4,sep="_")
# get the rows for the four damage states DS1_rows<-D\$Damage.state == "DS1"
DS2_rows<-D\$Damage.state == "DS2"
DS3_rows<-D\$Damage.state == "DS3"
DS4_rows<-D\$Damage.state == "DS4"
# step through all possible values of IM.type and Taxonomy for(IM in unique(D\$IM.type)) {  for(Tax in unique(D\$Taxonomy)) {
# get a logical vector of the rows to be used in this calculation
calc_rows<-D\$IM.type == IM & D\$Taxonomy == Tax
cat(IM,Tax,calc_rows,"\n")
# check that there are any such rows in the data frame
if(sum(calc_rows)) {
# if so, fill in the four values for these rows
D\$VC_1[calc_rows]<-sum(0.01 * (D[calc_rows & DS1_rows,calc_vars] -
D[calc_rows & DS2_rows,calc_vars]))
D\$VC_2[calc_rows]<-sum(0.02 * (D[calc_rows & DS2_rows,calc_vars] -
D[calc_rows & DS3_rows,calc_vars]))
D\$VC_3[calc_rows]<-sum(0.43 * (D[calc_rows & DS3_rows,calc_vars] -
D[calc_rows & DS4_rows,calc_vars]))
D\$VC_4[calc_rows]<-sum(D[calc_rows & DS4_rows,calc_vars])
}
}
}

Jim
```