2018-05-09 11:44:46 +02:00
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## ----setup, include = FALSE, results = 'markup'--------------------------
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knitr::opts_chunk$set(
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collapse = TRUE,
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comment = "#"
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)
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library(dplyr)
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library(AMR)
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## ---- echo = TRUE, results = 'hide'--------------------------------------
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2018-06-19 15:20:14 +02:00
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# just using base R
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2018-05-09 11:44:46 +02:00
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freq(septic_patients$sex)
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2018-07-01 21:40:37 +02:00
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# using base R to select the variable and pass it on with a pipe from the dplyr package
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2018-05-09 11:44:46 +02:00
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septic_patients$sex %>% freq()
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2018-07-01 21:40:37 +02:00
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# do it all with pipes, using the `select` function from the dplyr package
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2018-05-09 11:44:46 +02:00
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septic_patients %>%
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select(sex) %>%
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freq()
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2018-07-01 21:40:37 +02:00
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# or the preferred way: using a pipe to pass the variable on to the freq function
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septic_patients %>% freq(sex) # this also shows 'age' in the title
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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freq(septic_patients$sex)
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## ---- echo = TRUE, results = 'hide'--------------------------------------
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2018-07-01 21:40:37 +02:00
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my_patients <- septic_patients %>% left_join_microorganisms()
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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colnames(microorganisms)
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## ---- echo = TRUE--------------------------------------------------------
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dim(septic_patients)
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dim(my_patients)
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## ---- echo = TRUE--------------------------------------------------------
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2018-07-01 21:40:37 +02:00
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my_patients %>% freq(genus, species)
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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# # get age distribution of unique patients
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septic_patients %>%
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distinct(patient_id, .keep_all = TRUE) %>%
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2018-07-01 21:40:37 +02:00
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freq(age, nmax = 5)
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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2018-07-01 21:40:37 +02:00
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freq(hospital_id)
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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2018-07-01 21:40:37 +02:00
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freq(hospital_id, sort.count = TRUE)
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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select(amox) %>%
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freq()
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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select(date) %>%
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freq(nmax = 5)
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## ---- echo = TRUE--------------------------------------------------------
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2018-07-01 21:40:37 +02:00
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my_df <- septic_patients %>% freq(age)
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class(my_df)
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2018-05-09 11:44:46 +02:00
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2018-06-19 15:20:14 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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2018-07-01 21:40:37 +02:00
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dim(my_df)
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2018-06-19 15:20:14 +02:00
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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2018-07-01 21:40:37 +02:00
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freq(amox, na.rm = FALSE)
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2018-05-09 11:44:46 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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2018-07-01 21:40:37 +02:00
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septic_patients %>%
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freq(hospital_id, row.names = FALSE)
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2018-05-09 11:44:46 +02:00
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2018-07-01 21:40:37 +02:00
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## ---- echo = TRUE--------------------------------------------------------
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septic_patients %>%
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freq(hospital_id, markdown = TRUE)
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2018-05-09 11:44:46 +02:00
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## ---- echo = FALSE-------------------------------------------------------
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# this will print "2018" in 2018, and "2018-yyyy" after 2018.
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yrs <- c(2018:format(Sys.Date(), "%Y"))
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yrs <- c(min(yrs), max(yrs))
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yrs <- paste(unique(yrs), collapse = "-")
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