generated from opensafely/research-template
/
conversion_abtype_2021.R
99 lines (80 loc) · 3.88 KB
/
conversion_abtype_2021.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
library("tidyverse")
library('dplyr')
library('lubridate')
rm(list=ls())
setwd(here::here("output", "measures"))
# file list
csvFiles = c("input_ab_type_2021_2021-01-01.csv.gz","input_ab_type_2021_2021-02-01.csv.gz","input_ab_type_2021_2021-03-01.csv.gz",
"input_ab_type_2021_2021-04-01.csv.gz","input_ab_type_2021_2021-05-01.csv.gz","input_ab_type_2021_2021-06-01.csv.gz",
"input_ab_type_2021_2021-07-01.csv.gz","input_ab_type_2021_2021-08-01.csv.gz","input_ab_type_2021_2021-09-01.csv.gz",
"input_ab_type_2021_2021-10-01.csv.gz","input_ab_type_2021_2021-11-01.csv.gz","input_ab_type_2021_2021-12-01.csv.gz")
# variables
ab_date_12=paste0("AB_date_",rep(1:12))
ab_category=paste0("AB_date_",rep(1:12),"_indication")
ab_type=paste0("Ab_date_",rep(1:12),"_type")
# read columns
col_spec <-cols_only( patient_id = col_integer(),
AB_date_1 = col_date(format = ""),
AB_date_2 = col_date(format = ""),
AB_date_3 = col_date(format = ""),
AB_date_4 = col_date(format = ""),
AB_date_5 = col_date(format = ""),
AB_date_6 = col_date(format = ""),
AB_date_7 = col_date(format = ""),
AB_date_8 = col_date(format = ""),
AB_date_9 = col_date(format = ""),
AB_date_10 = col_date(format = ""),
AB_date_11 = col_date(format = ""),
AB_date_12 = col_date(format = ""),
AB_date_1_indication = col_character(),
AB_date_2_indication = col_character(),
AB_date_3_indication = col_character(),
AB_date_4_indication = col_character(),
AB_date_5_indication = col_character(),
AB_date_6_indication = col_character(),
AB_date_7_indication = col_character(),
AB_date_8_indication = col_character(),
AB_date_9_indication = col_character(),
AB_date_10_indication = col_character(),
AB_date_11_indication = col_character(),
AB_date_12_indication = col_character(),
Ab_date_1_type = col_character(),
Ab_date_2_type = col_character(),
Ab_date_3_type = col_character(),
Ab_date_4_type = col_character(),
Ab_date_5_type = col_character(),
Ab_date_6_type = col_character(),
Ab_date_7_type = col_character(),
Ab_date_8_type = col_character(),
Ab_date_9_type = col_character(),
Ab_date_10_type = col_character(),
Ab_date_11_type = col_character(),
Ab_date_12_type = col_character(),
age = col_integer(),
sex = col_character()
)
## save 2021 part 1 record
temp <- vector("list", length(csvFiles))
for (i in seq_along(csvFiles)){
df <- read_csv(csvFiles[i],
col_types = col_spec)
df1=df%>%select(patient_id,age,sex,ab_date_12)
colnames(df1)[4:15]=paste0("time",rep(1:12))
df1.1=df1%>%gather(times,date,paste0("time",rep(1:12)))
rm(df1)
df2=df%>%select(patient_id,age,sex,all_of(ab_type))
colnames(df2)[4:15]=paste0("time",rep(1:12))
df2.1=df2%>%gather(times,type,paste0("time",rep(1:12)))
rm(df2)
df3=df%>%select(patient_id,age,sex,all_of(ab_category))
colnames(df3)[4:15]=paste0("time",rep(1:12))
df3.1=df3%>%gather(times,infection,paste0("time",rep(1:12)))
rm(df3)
DF=merge(df1.1,df2.1,by=c("patient_id","age","sex","times"))
DF=merge(DF,df3.1,by=c("patient_id","age","sex","times"))
temp[[i]] <- DF
}
DF_ab <- bind_rows(temp)
DF_ab=DF_ab%>%filter(!is.na(date))
DF_ab$infection[DF_ab$infection == ""] <- NA
saveRDS(DF_ab, "abtype_2021.rds")