##Merge PCR and culture_2022
library(readxl)
pcr.22 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\PCR\\PCR_2022.xlsx")
cul.22 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\culture\\Culture_2022.xlsx")
#Conver Name to lowercase
library(dplyr) # for mutating
##
## 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
pcr.22 <- pcr.22 %>%
mutate(NAME = tolower(NAME))
cul.22 <- cul.22 %>%
mutate(FULL_NAME = tolower(FULL_NAME))
sq.22 <- merge(pcr.22, cul.22, by.x = "NAME", by.y = "FULL_NAME")
#Export dataframe to excel
#install.packages('writexl')
library(writexl)
write_xlsx(sq.22, "D:/2.RESEARCH/0. Projects/Sepsis_@Quick/sq.22.xlsx")
##Merge PCR and culture_2023
library(readxl)
pcr.23 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\PCR\\PCR_2023.xlsx")
cul.23 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\culture\\Culture_2023.xlsx")
library(dplyr)
library(tidyr)
library(magrittr)
##
## Attaching package: 'magrittr'
## The following object is masked from 'package:tidyr':
##
## extract
cul.23 %>% count(SPEC_TYPE)
## # A tibble: 46 × 2
## SPEC_TYPE n
## <chr> <int>
## 1 NA 7508
## 2 ab 41
## 3 ad 17
## 4 ak 15
## 5 as 180
## 6 ba 45
## 7 bi 55
## 8 bl 721
## 9 bo 1
## 10 bx 4
## # ℹ 36 more rows
library(dplyr) # for mutating
pcr.23 <- pcr.23 %>%
mutate(NAME = tolower(NAME))
cul.23 <- cul.23 %>%
mutate(FULL_NAME = tolower(FULL_NAME))
sq.23 <- merge(pcr.23, cul.23, by.x = "NAME", by.y = "FULL_NAME")
#Export dataframe to excel
#install.packages('writexl')
library(writexl)
write_xlsx(sq.23, "D:/2.RESEARCH/0. Projects/Sepsis_@Quick/sq.23.xlsx")
##Merge PCR and culture_2024_Culture data until 9.2024
library(readxl)
pcr.24 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\PCR\\PCR_2024.xlsx")
cul.24 <- read_xlsx("D:\\2.RESEARCH\\0. Projects\\Sepsis_@Quick\\Data\\culture\\Culture_2024.xlsx")
library(dplyr) # for mutating
pcr.24 <- pcr.24 %>%
mutate(NAME = tolower(NAME))
cul.24 <- cul.24 %>%
mutate(FULL_NAME = tolower(FULL_NAME))
sq.24 <- merge(pcr.24, cul.24, by.x = "NAME", by.y = "FULL_NAME")
#Export dataframe to excel
#install.packages('writexl')
library(writexl)
write_xlsx(sq.24, "D:/2.RESEARCH/0. Projects/Sepsis_@Quick/sq.24.xlsx")