Creating new variable based on two others

[redjoc]

Hi Community,

I'm a long time SAS user and I'm trying R, so I'm very new.

I'm looking to create a new variables "Best date" based on a two variables Incident date and Date Report. Incident date and Date report as their name implies are dates of when a particular report came in. Best date in this case is when there is no incident date but a report date.

In SAS it would look like this:

Best date=.;

if Incident date < Date Report then Best date= Incident date;
else if Incident date = NA then Best date = Date Report; #NA in this case is an empty cell#

I"m not even know where to start. Should I mutate the two variables into the Best date variable using dpyly library?

Please help. Thanks.

[mishabalyasin]

Take a look at dplyr::coalesce function. I think, it does what you want.

In R it would something like this:

your_dataset <- your_dataset %>%
    dplyr::mutate(Best_date = dplyr::coalesce(Incident_date, Date_report))

[redjoc]

Thanks for the reply!

I entered the code you provided:

my_data_set < - my_data_set %>% dplyr::mutate( Best date = dplyr::coalesce(Incident date, Date report))

But unfortunately, I get this error:
Error: unexpected symbol in "my_data_set <- ERP %>% dplyr::mutate(Best date"

[mishabalyasin]

Notice that variables in R can't have spaces in them and that is why I have Best_date = .... It is possible to have spaces in the name of the columns/variables, but overall it's a recipe for disaster down the line, so it's better to stick to convention and use alphanumeric characters + _.

[redjoc]

@mishabalyasin

your_dataset <- your_dataset %>% dplyr::mutate(Best_date = dplyr::coalesce(Incident_date, Date_report))

Thanks for the reply.

So I did what you said

Copy_merge_dataset <- Copy_merge_dataset %>%
dplyr::mutate(Best_date = dplyr::coalesce("Incident_Date", "Date_Report_Submitted"))

and got this error:

Error in mutate_(.data, .dots = compat_as_lazy_dots(...)) :
argument ".data" is missing, with no default

[mishabalyasin]

It's difficult to say for sure what is going wrong without reprex. As you can see, it works for me:

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

mtcars %>%
  dplyr::mutate(Best_cyl = dplyr::coalesce(cyl, disp))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb Best_cyl
#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4        6
#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4        6
#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1        4
#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1        6
#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2        8
#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1        6
#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4        8
#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2        4
#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2        4
#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4        6
#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4        6
#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3        8
#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3        8
#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3        8
#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4        8
#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4        8
#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4        8
#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1        4
#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2        4
#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1        4
#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1        4
#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2        8
#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2        8
#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4        8
#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2        8
#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1        4
#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2        4
#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2        4
#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4        8
#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6        6
#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8        8
#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2        4

^{Created on 2019-10-31 by the reprex package (v0.3.0)}

Try not using quotes in your dplyr::coalesce call.

[redjoc]

Hi!

I figured it out with this:

Merge_dataset$Best_Date  
       <- dplyr::coalesce(Merge_dataset$Incident_Date,    Merge_dataset$Date_Report_Submitted)

Worked without a hitch. Thanks for all your help!