Checking the Migration of Variables in Columns with the Same Id on R

Preprocessing in progress using R3.3.2 and package tidyverse.
Regarding the data below, we have investigated the same id multiple times (chousa has investigated the number of times).
I would like the data from the same survey item (Q1) to the 1st, 2nd, and 4th time since it was changed from 0 to 1.
How should I mute it?
Thank you for your cooperation.

ID Q1 Q6chousa...
1    0   3 　  1
1    1  23     2 
1    1
2    0  27     3 
2    0  28     4 
2    1  29     5

In this case,

ID change1change2... 
 1    　0        0
 1　　　1        0
 1      0        1
 2      0        0
 2      0        0
 2      1        0

I would like to make it

add
If Q1 says 0,0,1,1,1,1,10 for the same ID,

change1:0,0,1,0,0,0,0
change2—0,0,0,1,0,0,0
change3—0,0,0,0,0,1,0,0
change4—0,0,0,0,0,0,1,0
change5—0,0,0,0,0,0,0,0

I would like to make it

mute(change1=ifelse(Q1==1&Q1-lag(Q1)==1,1,0),
change2 = ifelse(Q1 == 1 & lag(change1) == 1,1,0),
change3=ifelse(Q1==1&lag(change2)==1,1,0),
change4=ifelse(Q1==1&lag(change3)==1,10))

I think I can go there by

 id change 1 change 2 change 3
 5      2       1       0       0
 5      3       0       1       0
 5      4       0       0       1

What I want you to do is

 id change 1 change 2 change 3
 5      2       0       0       1
 5      3       0       1       0
 5      4       1       0       0

It will be the opposite of .When I did group_by, it seems that the ascending and descending order of the ID is reversed. What should I do...

→ Not only group_by(ID), but also array(ID, chousa) resolved it.

2022-09-30 21:21

1 Answers

I don't understand the question properly, but if you do the following, the desired form will be printed.
(Determination of change1, change2 is hard to understand)

I think it's a lie to process each ID.

library(tidyverse)
data_frame(
     ID = c(rep(1,3), rep(2,3)),
     Q1 = c(0,1,1,0,0,1),
     chosa = c (1, 2, NA, 3, 4, 5)
%>% 
  # Aggregate by ID
  group_by(ID)%>% 
    # change1 —Subtract the value of Q1 in the next line from the Q1 in the target line and the Q1 in the target line.
    #   At this time, the first line of the ID is NA and 0 for continuous values.
    # change2 —Takes the difference between the value of change1 and the value of Q1 so that if Q1 follows the same value, it becomes 1.
  mute(change1 = Q1-lag(Q1),
         change2 = Q1-change1)%>% 
  ungroup()%>% 
  # treat NA as zero
  mute_at(num_range("change", 1:2), funs(ifelse(test=is.na(.), yes=0, no=.))%>% 
  select(ID, num_range("change", 1:2))

I don't understand the logic, so if the number of data increases, it might be ruined.For your information.

2022-09-30 21:21

If you have any answers or tips

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