Join the data set microorganisms easily to an existing data set or to a character vector.
Usage
inner_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
left_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
right_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
full_join_microorganisms(x, by = NULL, suffix = c("2", ""), ...)
semi_join_microorganisms(x, by = NULL, ...)
anti_join_microorganisms(x, by = NULL, ...)
Arguments
- x
existing data set to join, or character vector. In case of a character vector, the resulting data.frame will contain a column 'x' with these values.
- by
a variable to join by - if left empty will search for a column with class
mo
(created withas.mo()
) or will be"mo"
if that column name exists inx
, could otherwise be a column name ofx
with values that exist inmicroorganisms$mo
(such asby = "bacteria_id"
), or another column in microorganisms (but then it should be named, likeby = c("bacteria_id" = "fullname")
)- suffix
if there are non-joined duplicate variables in
x
andy
, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.- ...
ignored, only in place to allow future extensions
Details
Note: As opposed to the join()
functions of dplyr
, character vectors are supported and at default existing columns will get a suffix "2"
and the newly joined columns will not get a suffix.
If the dplyr
package is installed, their join functions will be used. Otherwise, the much slower merge()
and interaction()
functions from base R will be used.
Examples
left_join_microorganisms(as.mo("K. pneumoniae"))
#> ℹ Function `as.mo()` is uncertain about "K. pneumoniae" (assuming
#> Klebsiella pneumoniae). Run `mo_uncertainties()` to review this.
#> # A tibble: 1 × 16
#> mo fullname kingdom phylum class order family genus species subsp…¹
#> <mo> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 B_KLBSL_PNMN Klebsiel… Bacter… Prote… Gamm… Ente… Enter… Kleb… pneumo… ""
#> # … with 6 more variables: rank <chr>, ref <chr>, species_id <dbl>,
#> # source <chr>, prevalence <dbl>, snomed <list>, and abbreviated variable
#> # name ¹subspecies
left_join_microorganisms("B_KLBSL_PNMN")
#> # A tibble: 1 × 16
#> mo fullname kingdom phylum class order family genus species subsp…¹
#> <mo> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 B_KLBSL_PNMN Klebsiel… Bacter… Prote… Gamm… Ente… Enter… Kleb… pneumo… ""
#> # … with 6 more variables: rank <chr>, ref <chr>, species_id <dbl>,
#> # source <chr>, prevalence <dbl>, snomed <list>, and abbreviated variable
#> # name ¹subspecies
df <- data.frame(
date = seq(
from = as.Date("2018-01-01"),
to = as.Date("2018-01-07"),
by = 1
),
bacteria = as.mo(c(
"S. aureus", "MRSA", "MSSA", "STAAUR",
"E. coli", "E. coli", "E. coli"
)),
stringsAsFactors = FALSE
)
#> ℹ Function `as.mo()` is uncertain about "E. coli" (assuming Escherichia
#> coli) and "S. aureus" (assuming Staphylococcus aureus). Run
#> `mo_uncertainties()` to review these uncertainties.
colnames(df)
#> [1] "date" "bacteria"
df_joined <- left_join_microorganisms(df, "bacteria")
colnames(df_joined)
#> [1] "date" "bacteria" "fullname" "kingdom" "phylum"
#> [6] "class" "order" "family" "genus" "species"
#> [11] "subspecies" "rank" "ref" "species_id" "source"
#> [16] "prevalence" "snomed"
# \donttest{
if (require("dplyr")) {
example_isolates %>%
left_join_microorganisms() %>%
colnames()
}
#> Joining, by = "mo"
#> [1] "date" "patient" "age" "gender" "ward"
#> [6] "mo" "PEN" "OXA" "FLC" "AMX"
#> [11] "AMC" "AMP" "TZP" "CZO" "FEP"
#> [16] "CXM" "FOX" "CTX" "CAZ" "CRO"
#> [21] "GEN" "TOB" "AMK" "KAN" "TMP"
#> [26] "SXT" "NIT" "FOS" "LNZ" "CIP"
#> [31] "MFX" "VAN" "TEC" "TCY" "TGC"
#> [36] "DOX" "ERY" "CLI" "AZM" "IPM"
#> [41] "MEM" "MTR" "CHL" "COL" "MUP"
#> [46] "RIF" "fullname" "kingdom" "phylum" "class"
#> [51] "order" "family" "genus" "species" "subspecies"
#> [56] "rank" "ref" "species_id" "source" "prevalence"
#> [61] "snomed"
# }