conditionals (if, else if, else)

[elanlour]

Hi, people!
I will appreciate that someone could help me with this problem. I have a data with 4 columns and I want to create the 5 th new with some condictions.

This input data is in data.frame format is:

ALT_ORT,ALTGEOM,ALT_NORMAL,N,
2.8,,,-33.62,
3.2,,,-33.65,
,,46.4603,-7.88,
514.17,,,-6.09,

I tried to used this scrip

   if (is.na("ALTGEOM")==FALSE){
     t1$ALTGEOM2 <-  t1$ALTGEOM
     } else if (is.na("ALT_ORT")==FALSE) {
       t1$ALTGEOM2 <-t1$ALT_ORT+ t1$N
       } else {
         t1$ALTGEOM2 <-t1$ALT_NORMAL + t1$N
	}

And I would like this output file:

ALT_ORT,ALTGEOM,ALT_NORMAL,N,ALTGEOM2
2.8, , ,-33.62,-30.82
3.2, , ,-33.65,-30.45
, ,46.4603,-7.88, 38.5803
,514.17, , ,514.17

However, the real output is that:

ALT_ORT,ALTGEOM,ALT_NORMAL,N,ALTGEOM2
2.8, , ,-33.62,
3.2, , ,-33.65,
, ,46.4603,-7.88,
,514.17, , ,514.17

Does someone knows how can I do?

Thanks in advanced,

Elaine Loureiro

[andresrcs]

Hi, welcome!

To help us help you, could you please turn this into a proper reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[FJCC]

I took a stab at solving this without a reproducible example. If this does not solve your problem, please do make a reprex as andresrcs requested.

I used the case_when function of dplyr and I modified your description of the initial t1 to get the desired output.

library(dplyr)
t1 <- read.csv("c:/users/fjcc/Documents/R/Play/Dummy.csv")
t1
#>   ALT_ORT ALTGEOM ALT_NORMAL      N
#> 1     2.8      NA         NA -33.62
#> 2     3.2      NA         NA -33.65
#> 3      NA      NA    46.4603  -7.88
#> 4      NA  514.17         NA  -6.09
t1$ALTGEOM2 <- case_when(
  !is.na(t1$ALTGEOM) ~ t1$ALTGEOM, 
  !is.na(t1$ALT_ORT) ~ t1$ALT_ORT + t1$N,
  TRUE ~ t1$ALT_NORMAL + t1$N
  )


t1
#>   ALT_ORT ALTGEOM ALT_NORMAL      N ALTGEOM2
#> 1     2.8      NA         NA -33.62 -30.8200
#> 2     3.2      NA         NA -33.65 -30.4500
#> 3      NA      NA    46.4603  -7.88  38.5803
#> 4      NA  514.17         NA  -6.09 514.1700

^{Created on 2019-09-23 by the reprex package (v0.2.1)}

[elanlour]

I tested this solution and solve the problem. Thanks a lot!

[elanlour]

Thanks for your orientation, however FJCC solved the problem. In the next question, I will use the procedure and generate a good dataset for testing.

Thanks a lot!

elanlour