I have received an data frame for analysis, each observation is a row, with 120 variables. Unfortunately I have not received an observation ID variable that uniquely identifies each observations.
I was thinking maybe I could concatenate all columns to a string and hash this string to obtain a unique ID.
How can I do this without specifying all variables like with paste(). Or is there another solution?
The data can contain NA
here is the sample dataset
structure(list(Class = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L,
4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L,
4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L), levels = c("1st", "2nd",
"3rd", "Crew"), class = "factor"), Sex = structure(c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), levels = c("Male",
"Female"), class = "factor"), Age = structure(c(1L, NA, 1L, NA,
1L, NA, 1L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 2L, NA, 1L, 1L, 1L, NA,
NA, 1L, 1L, 1L, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA), levels = c("Child",
"Adult"), class = "factor"), Survived = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("No",
"Yes"), class = "factor"), Freq = c(0, 0, 35, 0, 0, 0, 17, 0,
118, 154, 387, 670, 4, 13, 89, 3, 5, 11, 13, 0, 1, 13, 14, 0,
57, 14, 75, 192, 140, 80, 76, 20)), row.names = c(NA, -32L), class = "data.frame")
CodePudding user response：
Maybe you want to use the unique_identifier function from the udpipe package which does:
Create a unique identifier for each combination of fields in a data frame. This unique identifier is unique for each combination of the elements of the fields. The generated identifier is like a primary key or a secondary key on a table. This is just a small wrapper around frank
Here reproducible example:
df <- structure(list(Class = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L,
4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L,
4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L), levels = c("1st", "2nd",
"3rd", "Crew"), class = "factor"), Sex = structure(c(1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), levels = c("Male",
"Female"), class = "factor"), Age = structure(c(1L, NA, 1L, NA,
1L, NA, 1L, 1L, 2L, 2L, NA, 2L, 2L, 2L, 2L, NA, 1L, 1L, 1L, NA,
NA, 1L, 1L, 1L, NA, 2L, 2L, 2L, 2L, 2L, 2L, NA), levels = c("Child",
"Adult"), class = "factor"), Survived = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("No",
"Yes"), class = "factor"), Freq = c(0, 0, 35, 0, 0, 0, 17, 0,
118, 154, 387, 670, 4, 13, 89, 3, 5, 11, 13, 0, 1, 13, 14, 0,
57, 14, 75, 192, 140, 80, 76, 20)), row.names = c(NA, -32L), class = "data.frame")
library(udpipe)
#> Warning: package 'udpipe' was built under R version 4.1.2
df$ID <- unique_identifier(df, fields = colnames(df))
df
#> Class Sex Age Survived Freq ID
#> 1 1st Male Child No 0 1
#> 2 2nd Male <NA> No 0 12
#> 3 3rd Male Child No 35 17
#> 4 Crew Male <NA> No 0 27
#> 5 1st Female Child No 0 5
#> 6 2nd Female <NA> No 0 16
#> 7 3rd Female Child No 17 21
#> 8 Crew Female Child No 0 29
#> 9 1st Male Adult No 118 3
#> 10 2nd Male Adult No 154 10
#> 11 3rd Male <NA> No 387 20
#> 12 Crew Male Adult No 670 25
#> 13 1st Female Adult No 4 6
#> 14 2nd Female Adult No 13 14
#> 15 3rd Female Adult No 89 23
#> 16 Crew Female <NA> No 3 31
#> 17 1st Male Child Yes 5 2
#> 18 2nd Male Child Yes 11 9
#> 19 3rd Male Child Yes 13 18
#> 20 Crew Male <NA> Yes 0 28
#> 21 1st Female <NA> Yes 1 8
#> 22 2nd Female Child Yes 13 13
#> 23 3rd Female Child Yes 14 22
#> 24 Crew Female Child Yes 0 30
#> 25 1st Male <NA> Yes 57 4
#> 26 2nd Male Adult Yes 14 11
#> 27 3rd Male Adult Yes 75 19
#> 28 Crew Male Adult Yes 192 26
#> 29 1st Female Adult Yes 140 7
#> 30 2nd Female Adult Yes 80 15
#> 31 3rd Female Adult Yes 76 24
#> 32 Crew Female <NA> Yes 20 32
Created on 2022-07-24 by the reprex package (v2.0.1)
CodePudding user response：
Another option is to use unclass on factors (i.e., after pasting all columns together using Reduce), which will convert the factors to their numbers.
df$ID <- c(unclass(as.factor(Reduce(paste, df))))
Output
Class Sex Age Survived Freq ID
1 1st Male Child No 0 6
2 2nd Male <NA> No 0 16
3 3rd Male Child No 35 22
4 Crew Male <NA> No 0 31
5 1st Female Child No 0 3
6 2nd Female <NA> No 0 12
7 3rd Female Child No 17 19
8 Crew Female Child No 0 25
9 1st Male Adult No 118 5
10 2nd Male Adult No 154 13
11 3rd Male <NA> No 387 24
12 Crew Male Adult No 670 29
13 1st Female Adult No 4 1
14 2nd Female Adult No 13 9
15 3rd Female Adult No 89 17
16 Crew Female <NA> No 3 27
17 1st Male Child Yes 5 7
18 2nd Male Child Yes 11 15
19 3rd Male Child Yes 13 23
20 Crew Male <NA> Yes 0 32
21 1st Female <NA> Yes 1 4
22 2nd Female Child Yes 13 11
23 3rd Female Child Yes 14 20
24 Crew Female Child Yes 0 26
25 1st Male <NA> Yes 57 8
26 2nd Male Adult Yes 14 14
27 3rd Male Adult Yes 75 21
28 Crew Male Adult Yes 192 30
29 1st Female Adult Yes 140 2
30 2nd Female Adult Yes 80 10
31 3rd Female Adult Yes 76 18
32 Crew Female <NA> Yes 20 28