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 ofxwith 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
xandy, 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"))
#> # A tibble: 1 × 22
#> mo fullname status kingdom phylum class order family genus species
#> <mo> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…
#> # … with 12 more variables: subspecies <chr>, rank <chr>, ref <chr>,
#> # source <chr>, lpsn <chr>, lpsn_parent <chr>, lpsn_renamed_to <chr>,
#> # gbif <chr>, gbif_parent <chr>, gbif_renamed_to <chr>, prevalence <dbl>,
#> # snomed <list>
left_join_microorganisms("B_KLBSL_PNMN")
#> # A tibble: 1 × 22
#> mo fullname status kingdom phylum class order family genus species
#> <mo> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 B_KLBSL_PNMN Klebsiell… accep… Bacter… Pseud… Gamm… Ente… Enter… Kleb… pneumo…
#> # … with 12 more variables: subspecies <chr>, rank <chr>, ref <chr>,
#> # source <chr>, lpsn <chr>, lpsn_parent <chr>, lpsn_renamed_to <chr>,
#> # gbif <chr>, gbif_parent <chr>, gbif_renamed_to <chr>, prevalence <dbl>,
#> # snomed <list>
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
)
colnames(df)
#> [1] "date" "bacteria"
df_joined <- left_join_microorganisms(df, "bacteria")
colnames(df_joined)
#> [1] "date" "bacteria" "fullname" "status"
#> [5] "kingdom" "phylum" "class" "order"
#> [9] "family" "genus" "species" "subspecies"
#> [13] "rank" "ref" "source" "lpsn"
#> [17] "lpsn_parent" "lpsn_renamed_to" "gbif" "gbif_parent"
#> [21] "gbif_renamed_to" "prevalence" "snomed"
# \donttest{
if (require("dplyr")) {
example_isolates %>%
left_join_microorganisms() %>%
colnames()
}
#> Joining, by = "mo"
#> [1] "date" "patient" "age" "gender"
#> [5] "ward" "mo" "PEN" "OXA"
#> [9] "FLC" "AMX" "AMC" "AMP"
#> [13] "TZP" "CZO" "FEP" "CXM"
#> [17] "FOX" "CTX" "CAZ" "CRO"
#> [21] "GEN" "TOB" "AMK" "KAN"
#> [25] "TMP" "SXT" "NIT" "FOS"
#> [29] "LNZ" "CIP" "MFX" "VAN"
#> [33] "TEC" "TCY" "TGC" "DOX"
#> [37] "ERY" "CLI" "AZM" "IPM"
#> [41] "MEM" "MTR" "CHL" "COL"
#> [45] "MUP" "RIF" "fullname" "status"
#> [49] "kingdom" "phylum" "class" "order"
#> [53] "family" "genus" "species" "subspecies"
#> [57] "rank" "ref" "source" "lpsn"
#> [61] "lpsn_parent" "lpsn_renamed_to" "gbif" "gbif_parent"
#> [65] "gbif_renamed_to" "prevalence" "snomed"
# }