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I had written some code months ago to find the days until the next visit and the days since the last visit to track patient progress and identify missed appointments. This code worked beautifully and gave the correct number of days (I verified a sample by hand) but now it isn't working. It appears as though the "Group_by()" command is being ignored and it is simply calculating the number of days between the observations as they are ordered in R rather than giving an "NA" at the beginning and end of each grouping. I guess I'm mostly just confused why this was working but then stopped.

Code:

    dd5 <- dd5 %>% 
  arrange(PatientID, GroupingUid, VisitDate) %>%
  group_by(GroupingUid) %>%
  mutate(Days.Until.Next.Visit = as.numeric(lead(VisitDate) - VisitDate))


dd5 <- dd5 %>% 
  arrange(PatientID, GroupingUid, VisitDate) %>%
  group_by(GroupingUid) %>%
  mutate(Days.Since.Last.Visit = as.numeric(VisitDate - lag(VisitDate)))

UPDATE: I have tried ungrouping and then arranging and regrouping, I tried grouping and then arranging, and I have removed the as.numeric() but not had any success.

GroupingUID and PatientUID are unique identifiers that I am using to track each patient/injury. Each combo of GroupingUID and PatientID should have the days calculated separately. VisitDate is obviously the date. 

83515888-E9C2-4B71-87EB-E954182DED88    1   8/22/2017   38  5
86169252-F2CD-4EDF-843F-6946AD45376A    1   9/29/2017   -56 38
B8498C0E-CF25-4F05-A7AC-DFECE1252183    1   8/4/2017    25  -56
BEABCA88-E3EB-4D48-B52B-D5639C527141    1   8/29/2017   2   25
DE7493C0-F72C-44D8-8469-9AA30662769D    1   8/31/2017   -2  2
EE720E94-9B1F-4350-A1B5-87E71BF40E35    1   8/29/2017   -32 -2
3970FF5F-4FEB-4509-A94E-0678000C505A    10  7/28/2017   0   -32
461BC1C4-F07C-4F42-BD8E-7545644FF4BA    10  7/28/2017   54  0
0656001E-2289-4B5D-B49A-CB6F57BD8E89    100 5/8/2018    7   13
0656001E-2289-4B5D-B49A-CB6F57BD8E89    100 5/15/2018   7   7
0656001E-2289-4B5D-B49A-CB6F57BD8E89    100 5/22/2018   -33 7
0286CDBF-1F52-4074-94B6-AE541E0DC9BF    10006   4/19/2018   6   -33
0286CDBF-1F52-4074-94B6-AE541E0DC9BF    10006   4/25/2018   8   6
0286CDBF-1F52-4074-94B6-AE541E0DC9BF    10006   7/12/2018   4   7
0286CDBF-1F52-4074-94B6-AE541E0DC9BF    10006   7/16/2018   -88 4
04A80019-561F-4CD4-B2D5-CAE059051750    10006   4/19/2018   6   -88
04A80019-561F-4CD4-B2D5-CAE059051750    10006   4/25/2018   8   6
F75FC4A1-587A-414E-BA35-9E5A6948F3FC    10006   6/28/2018   7   7
F75FC4A1-587A-414E-BA35-9E5A6948F3FC    10006   7/5/2018    7   7
F75FC4A1-587A-414E-BA35-9E5A6948F3FC    10006   7/12/2018   -300    7
09772AD1-2096-4C56-83AB-08CF9876ADDC    102 9/15/2017   7   -300
87C3C708-64F6-4321-9D98-F258B04B7E39    102 10/27/2017  7   7
87C3C708-64F6-4321-9D98-F258B04B7E39    102 11/3/2017   -49 7
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 9/15/2017   7   -49
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 9/22/2017   7   7
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 9/29/2017   14  7
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 10/13/2017  7   14
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 10/20/2017  7   7
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 10/27/2017  7   7
BE2EFB0A-A1D8-49E6-88CF-D9818D1EF60D    102 11/3/2017   -37 7
0B8DAD9F-2141-42A4-BBC8-F026DA4CB24A    103 9/27/2017   0   -37
440B3D2F-7E4E-42AE-9274-CCF751A10A94    103 9/27/2017   0   0
70112B85-7396-4A72-8853-B308D061383C    103 9/27/2017   0   0
889AB652-42C6-409F-A389-1CA96E66997B    103 9/27/2017   0   0
AAD6D986-80FE-4143-8ABF-BCADE73AB2EA    103 9/27/2017   0   0
C03778F8-1499-4FB0-99CC-D3A3B1143E4F    103 9/27/2017   0   0
C7E21544-96F4-46CB-87F5-11D882352FE0    103 9/27/2017   0   0
DD401067-3FCA-4828-8765-635E82181D1E    103 9/27/2017   0   0
F873284F-B86E-47CA-BA68-3AD4650CD72F    103 9/27/2017   -6  0
0B1CC77A-BADC-4971-AB14-7A5FB982DC4C    104 9/21/2017   7   -6
0B1CC77A-BADC-4971-AB14-7A5FB982DC4C    104 9/28/2017   14  7
0B1CC77A-BADC-4971-AB14-7A5FB982DC4C    104 10/12/2017  0   14
352F0DFE-C06F-46CC-AFE5-F6B8929FB31B    104 10/12/2017  -14 0
regents
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  • Your `VisitDate` column is not sorted correctly. The calculations however appear to be working right given the current order of the data. You may need to `arrange` after `group_by` – Mako212 Sep 17 '18 at 18:29
  • Or just make `ungroup` your first statement before `arrange`. `group_by` doesn't re-sort your data, but it's possible you have already grouped `dd5`, causing the `arrange` call to provide an unexpected result. – Mako212 Sep 17 '18 at 18:33
  • I've tried both of your solutions and neither of them offered any improvement, thank you though @Mako212 – regents Sep 17 '18 at 18:48

1 Answers1

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In my original code I was using the following packages to accomplish several things:

library(stringi)
library(stringr)
library(lubridate)
library(plyr)
library(dplyr)
library(tidyverse)
library(viridis).

It appears as though tidyverse was suppressing the mutate function from dpylr. removing all of the packages and then calling them after the calculations appears to have fixed the issue.

regents
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