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< h1 > AMR plots with < code > ggplot2< / code > < / h1 >
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< div class = "hidden name" > < code > ggplot_rsi.Rd< / code > < / div >
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< p > Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal < code > < a href = 'https://ggplot2.tidyverse.org/reference/ggplot.html' > ggplot< / a > 2< / code > functions.< / p >
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< / div >
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< pre class = "usage" > < span class = 'fu' > ggplot_rsi< / span > (< span class = 'no' > data< / span > , < span class = 'kw' > position< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'st' > "antibiotic"< / span > ,
< span class = 'kw' > fill< / span > < span class = 'kw' > =< / span > < span class = 'st' > "interpretation"< / span > , < span class = 'kw' > facet< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > breaks< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/seq' > seq< / a > < / span > (< span class = 'fl' > 0< / span > , < span class = 'fl' > 1< / span > , < span class = 'fl' > 0.1< / span > ),
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< span class = 'kw' > limits< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > translate_ab< / span > < span class = 'kw' > =< / span > < span class = 'st' > "name"< / span > , < span class = 'kw' > combine_SI< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > ,
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< span class = 'kw' > combine_IR< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > , < span class = 'kw' > language< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'translate.html' > get_locale< / a > < / span > (), < span class = 'kw' > nrow< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > ,
< span class = 'kw' > colours< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'kw' > S< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#61a8ff"< / span > , < span class = 'kw' > SI< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#61a8ff"< / span > , < span class = 'kw' > I< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#61f7ff"< / span > , < span class = 'kw' > IR< / span > < span class = 'kw' > =< / span >
< span class = 'st' > "#ff6961"< / span > , < span class = 'kw' > R< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#ff6961"< / span > ), < span class = 'kw' > datalabels< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > , < span class = 'kw' > datalabels.size< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 2.5< / span > ,
< span class = 'kw' > datalabels.colour< / span > < span class = 'kw' > =< / span > < span class = 'st' > "gray15"< / span > , < span class = 'kw' > title< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > subtitle< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > ,
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< span class = 'kw' > caption< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > x.title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "Antimicrobial"< / span > , < span class = 'kw' > y.title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "Proportion"< / span > ,
< span class = 'no' > ...< / span > )
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< span class = 'fu' > geom_rsi< / span > (< span class = 'kw' > position< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'st' > "antibiotic"< / span > , < span class = 'st' > "interpretation"< / span > ),
< span class = 'kw' > fill< / span > < span class = 'kw' > =< / span > < span class = 'st' > "interpretation"< / span > , < span class = 'kw' > translate_ab< / span > < span class = 'kw' > =< / span > < span class = 'st' > "name"< / span > ,
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< span class = 'kw' > language< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'translate.html' > get_locale< / a > < / span > (), < span class = 'kw' > combine_SI< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > , < span class = 'kw' > combine_IR< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > ,
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< span class = 'no' > ...< / span > )
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< span class = 'fu' > facet_rsi< / span > (< span class = 'kw' > facet< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'st' > "interpretation"< / span > , < span class = 'st' > "antibiotic"< / span > ), < span class = 'kw' > nrow< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > )
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< span class = 'fu' > scale_y_percent< / span > (< span class = 'kw' > breaks< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/seq' > seq< / a > < / span > (< span class = 'fl' > 0< / span > , < span class = 'fl' > 1< / span > , < span class = 'fl' > 0.1< / span > ), < span class = 'kw' > limits< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > )
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< span class = 'fu' > scale_rsi_colours< / span > (< span class = 'kw' > colours< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'kw' > S< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#61a8ff"< / span > , < span class = 'kw' > SI< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#61a8ff"< / span > , < span class = 'kw' > I< / span > < span class = 'kw' > =< / span >
< span class = 'st' > "#61f7ff"< / span > , < span class = 'kw' > IR< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#ff6961"< / span > , < span class = 'kw' > R< / span > < span class = 'kw' > =< / span > < span class = 'st' > "#ff6961"< / span > ))
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< span class = 'fu' > theme_rsi< / span > ()
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< span class = 'fu' > labels_rsi_count< / span > (< span class = 'kw' > position< / span > < span class = 'kw' > =< / span > < span class = 'kw' > NULL< / span > , < span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'st' > "antibiotic"< / span > ,
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< span class = 'kw' > translate_ab< / span > < span class = 'kw' > =< / span > < span class = 'st' > "name"< / span > , < span class = 'kw' > combine_SI< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > , < span class = 'kw' > combine_IR< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > ,
< span class = 'kw' > datalabels.size< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 3< / span > , < span class = 'kw' > datalabels.colour< / span > < span class = 'kw' > =< / span > < span class = 'st' > "gray15"< / span > )< / pre >
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< h2 class = "hasAnchor" id = "arguments" > < a class = "anchor" href = "#arguments" > < / a > Arguments< / h2 >
< table class = "ref-arguments" >
< colgroup > < col class = "name" / > < col class = "desc" / > < / colgroup >
< tr >
< th > data< / th >
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< td > < p > a < code > data.frame< / code > with column(s) of class < code > "rsi"< / code > (see < code > < a href = 'as.rsi.html' > as.rsi< / a > < / code > )< / p > < / td >
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< / tr >
< tr >
< th > position< / th >
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< td > < p > position adjustment of bars, either < code > "fill"< / code > (default when < code > fun< / code > is < code > < a href = 'count.html' > count_df< / a > < / code > ), < code > "stack"< / code > (default when < code > fun< / code > is < code > < a href = 'portion.html' > portion_df< / a > < / code > ) or < code > "dodge"< / code > < / p > < / td >
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< / tr >
< tr >
< th > x< / th >
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< td > < p > variable to show on x axis, either < code > "antibiotic"< / code > (default) or < code > "interpretation"< / code > or a grouping variable< / p > < / td >
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< / tr >
< tr >
< th > fill< / th >
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< td > < p > variable to categorise using the plots legend, either < code > "antibiotic"< / code > (default) or < code > "interpretation"< / code > or a grouping variable< / p > < / td >
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< / tr >
< tr >
< th > facet< / th >
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< td > < p > variable to split plots by, either < code > "interpretation"< / code > (default) or < code > "antibiotic"< / code > or a grouping variable< / p > < / td >
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< / tr >
< tr >
< th > breaks< / th >
< td > < p > numeric vector of positions< / p > < / td >
< / tr >
< tr >
< th > limits< / th >
< td > < p > numeric vector of length two providing limits of the scale, use < code > NA< / code > to refer to the existing minimum or maximum< / p > < / td >
< / tr >
< tr >
< th > translate_ab< / th >
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< td > < p > a column name of the < code > < a href = 'antibiotics.html' > antibiotics< / a > < / code > data set to translate the antibiotic abbreviations to, using < code > < a href = 'ab_property.html' > ab_property< / a > < / code > < / p > < / td >
< / tr >
< tr >
< th > combine_SI< / th >
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< td > < p > a logical to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant). This used to be the parameter < code > combine_IR< / code > , but this now follows the redefinition by EUCAST about the interpretion of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. Default is < code > TRUE< / code > .< / p > < / td >
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< / tr >
< tr >
< th > combine_IR< / th >
< td > < p > a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. I+R (susceptible vs. non-susceptible). This is outdated, see parameter < code > combine_SI< / code > .< / p > < / td >
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< / tr >
< tr >
< th > language< / th >
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< td > < p > language of the returned text, defaults to system language (see < code > < a href = 'translate.html' > get_locale< / a > < / code > ) and can also be set with < code > < a href = 'https://www.rdocumentation.org/packages/base/topics/options' > getOption< / a > ("AMR_locale")< / code > . Use < code > language = NULL< / code > or < code > language = ""< / code > to prevent translation.< / p > < / td >
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< / tr >
< tr >
< th > nrow< / th >
< td > < p > (when using < code > facet< / code > ) number of rows< / p > < / td >
< / tr >
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< tr >
< th > colours< / th >
< td > < p > a named vector with colours for the bars. The names must be one or more of: S, SI, I, IR, R or be < code > FALSE< / code > to use default < code > ggplot2< / code > colours.< / p > < / td >
< / tr >
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< tr >
< th > datalabels< / th >
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< td > < p > show datalabels using < code > labels_rsi_count< / code > < / p > < / td >
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< / tr >
< tr >
< th > datalabels.size< / th >
< td > < p > size of the datalabels< / p > < / td >
< / tr >
< tr >
< th > datalabels.colour< / th >
< td > < p > colour of the datalabels< / p > < / td >
< / tr >
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< tr >
< th > title< / th >
< td > < p > text to show as title of the plot< / p > < / td >
< / tr >
< tr >
< th > subtitle< / th >
< td > < p > text to show as subtitle of the plot< / p > < / td >
< / tr >
< tr >
< th > caption< / th >
< td > < p > text to show as caption of the plot< / p > < / td >
< / tr >
< tr >
< th > x.title< / th >
< td > < p > text to show as x axis description< / p > < / td >
< / tr >
< tr >
< th > y.title< / th >
< td > < p > text to show as y axis description< / p > < / td >
< / tr >
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< tr >
< th > ...< / th >
< td > < p > other parameters passed on to < code > geom_rsi< / code > < / p > < / td >
< / tr >
< / table >
< h2 class = "hasAnchor" id = "details" > < a class = "anchor" href = "#details" > < / a > Details< / h2 >
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< p > At default, the names of antibiotics will be shown on the plots using < code > < a href = 'ab_property.html' > ab_name< / a > < / code > . This can be set with the < code > translate_ab< / code > parameter. See < code > < a href = 'count.html' > count_df< / a > < / code > .< / p >
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< p > < strong > The functions< / strong > < br / >
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< code > geom_rsi< / code > will take any variable from the data that has an < code > rsi< / code > class (created with < code > < a href = 'as.rsi.html' > as.rsi< / a > < / code > ) using < code > < a href = 'portion.html' > rsi_df< / a > < / code > and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.< / p >
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< p > < code > facet_rsi< / code > creates 2d plots (at default based on S/I/R) using < code > < a href = 'https://ggplot2.tidyverse.org/reference/facet_wrap.html' > facet_wrap< / a > < / code > .< / p >
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< p > < code > scale_y_percent< / code > transforms the y axis to a 0 to 100% range using < code > scale_continuous< / code > .< / p >
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< p > < code > scale_rsi_colours< / code > sets colours to the bars: pastel blue for S, pastel turquoise for I and pastel red for R, using < code > scale_brewer< / code > .< / p >
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< p > < code > theme_rsi< / code > is a < code > ggplot < a href = 'https://ggplot2.tidyverse.org/reference/theme.html' > theme< / a > < / code > with minimal distraction.< / p >
< p > < code > labels_rsi_count< / code > print datalabels on the bars with percentage and amount of isolates using < code > < a href = 'https://ggplot2.tidyverse.org/reference/geom_text.html' > geom_text< / a > < / code > < / p >
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< p > < code > ggplot_rsi< / code > is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (< code > %> %< / code > ). See Examples.< / p >
2019-01-02 23:24:07 +01:00
< h2 class = "hasAnchor" id = "read-more-on-our-website-" > < a class = "anchor" href = "#read-more-on-our-website-" > < / a > Read more on our website!< / h2 >
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< p > On our website < a href = 'https://msberends.gitlab.io/AMR' > https://msberends.gitlab.io/AMR< / a > you can find < a href = 'https://msberends.gitlab.io/AMR/articles/AMR.html' > a tutorial< / a > about how to conduct AMR analysis, the < a href = 'https://msberends.gitlab.io/AMR/reference' > complete documentation of all functions< / a > (which reads a lot easier than here in R) and < a href = 'https://msberends.gitlab.io/AMR/articles/WHONET.html' > an example analysis using WHONET data< / a > .< / p >
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< h2 class = "hasAnchor" id = "examples" > < a class = "anchor" href = "#examples" > < / a > Examples< / h2 >
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< pre class = "examples" > < span class = 'co' > # NOT RUN {< / span >
< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/library' > library< / a > < / span > (< span class = 'no' > dplyr< / span > )
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< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/library' > library< / a > < / span > (< span class = 'no' > ggplot2< / span > )
< span class = 'co' > # get antimicrobial results for drugs against a UTI:< / span >
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< span class = 'fu' > < a href = 'https://ggplot2.tidyverse.org/reference/ggplot.html' > ggplot< / a > < / span > (< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span > < span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > )) +
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< span class = 'fu' > geom_rsi< / span > ()
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< span class = 'co' > # prettify the plot using some additional functions:< / span >
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< span class = 'no' > df< / span > < span class = 'kw' > < -< / span > < span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span > < span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > )
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< span class = 'fu' > < a href = 'https://ggplot2.tidyverse.org/reference/ggplot.html' > ggplot< / a > < / span > (< span class = 'no' > df< / span > ) +
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< span class = 'fu' > geom_rsi< / span > () +
< span class = 'fu' > scale_y_percent< / span > () +
< span class = 'fu' > scale_rsi_colours< / span > () +
< span class = 'fu' > labels_rsi_count< / span > () +
2019-01-02 23:24:07 +01:00
< span class = 'fu' > theme_rsi< / span > ()
2018-12-23 21:26:21 +01:00
< span class = 'co' > # or better yet, simplify this using the wrapper function - a single command:< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2019-01-02 23:24:07 +01:00
< span class = 'fu' > ggplot_rsi< / span > ()
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< span class = 'co' > # get only portions and no counts:< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2019-06-27 11:57:45 +02:00
< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > datalabels< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
2019-01-02 23:24:07 +01:00
2018-12-23 21:26:21 +01:00
< span class = 'co' > # add other ggplot2 parameters as you like:< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
2019-05-10 16:44:59 +02:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > width< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 0.5< / span > ,
< span class = 'kw' > colour< / span > < span class = 'kw' > =< / span > < span class = 'st' > "black"< / span > ,
< span class = 'kw' > size< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 1< / span > ,
< span class = 'kw' > linetype< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 2< / span > ,
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< span class = 'kw' > alpha< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 0.25< / span > )
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > ) < span class = 'kw' > %> %< / span >
< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > colours< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'kw' > SI< / span > < span class = 'kw' > =< / span > < span class = 'st' > "yellow"< / span > ))
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< span class = 'co' > # resistance of ciprofloxacine per age group< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
2019-01-29 20:20:09 +01:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/mutate.html' > mutate< / a > < / span > (< span class = 'kw' > first_isolate< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'first_isolate.html' > first_isolate< / a > < / span > (< span class = 'no' > .< / span > )) < span class = 'kw' > %> %< / span >
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/filter.html' > filter< / a > < / span > (< span class = 'no' > first_isolate< / span > < span class = 'kw' > ==< / span > < span class = 'fl' > TRUE< / span > ,
2018-12-31 01:48:53 +01:00
< span class = 'no' > mo< / span > < span class = 'kw' > ==< / span > < span class = 'fu' > < a href = 'as.mo.html' > as.mo< / a > < / span > (< span class = 'st' > "E. coli"< / span > )) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # `age_group` is also a function of this package:< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/group_by.html' > group_by< / a > < / span > (< span class = 'kw' > age_group< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'age_groups.html' > age_groups< / a > < / span > (< span class = 'no' > age< / span > )) < span class = 'kw' > %> %< / span >
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > age_group< / span > ,
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< span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
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< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'st' > "age_group"< / span > )
< span class = 'co' > # }< / span > < span class = 'co' > # NOT RUN {< / span >
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< span class = 'co' > # for colourblind mode, use divergent colours from the viridis package:< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
2019-05-10 16:44:59 +02:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2019-06-22 14:49:12 +02:00
< span class = 'fu' > ggplot_rsi< / span > () + < span class = 'fu' > < a href = 'https://ggplot2.tidyverse.org/reference/scale_viridis.html' > scale_fill_viridis_d< / a > < / span > ()
2019-05-31 20:25:57 +02:00
< span class = 'co' > # a shorter version which also adjusts data label colours:< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > colours< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
2019-01-02 23:24:07 +01:00
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< span class = 'co' > # it also supports groups (don't forget to use the group var on `x` or `facet`):< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
2019-05-10 16:44:59 +02:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > hospital_id< / span > , < span class = 'no' > AMX< / span > , < span class = 'no' > NIT< / span > , < span class = 'no' > FOS< / span > , < span class = 'no' > TMP< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2019-01-29 20:20:09 +01:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/group_by.html' > group_by< / a > < / span > (< span class = 'no' > hospital_id< / span > ) < span class = 'kw' > %> %< / span >
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< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'st' > "hospital_id"< / span > ,
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< span class = 'kw' > facet< / span > < span class = 'kw' > =< / span > < span class = 'st' > "antibiotic"< / span > ,
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< span class = 'kw' > nrow< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 1< / span > ,
< span class = 'kw' > title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "AMR of Anti-UTI Drugs Per Hospital"< / span > ,
< span class = 'kw' > x.title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "Hospital"< / span > ,
< span class = 'kw' > datalabels< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'co' > # genuine analysis: check 3 most prevalent microorganisms< / span >
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< span class = 'no' > example_isolates< / span > < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # create new bacterial ID's, with all CoNS under the same group (Becker et al.)< / span >
2019-01-29 20:20:09 +01:00
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/mutate.html' > mutate< / a > < / span > (< span class = 'kw' > mo< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'as.mo.html' > as.mo< / a > < / span > (< span class = 'no' > mo< / span > , < span class = 'kw' > Becker< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > )) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # filter on top three bacterial ID's< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/filter.html' > filter< / a > < / span > (< span class = 'no' > mo< / span > < span class = 'kw' > %in%< / span > < span class = 'fu' > top_freq< / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/clean/topics/freq' > freq< / a > < / span > (< span class = 'no' > .< / span > $< span class = 'no' > mo< / span > ), < span class = 'fl' > 3< / span > )) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # filter on first isolates< / span >
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< span class = 'fu' > < a href = 'first_isolate.html' > filter_first_isolate< / a > < / span > () < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # get short MO names (like "E. coli")< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/mutate.html' > mutate< / a > < / span > (< span class = 'kw' > bug< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'mo_property.html' > mo_shortname< / a > < / span > (< span class = 'no' > mo< / span > , < span class = 'kw' > Becker< / span > < span class = 'kw' > =< / span > < span class = 'fl' > TRUE< / span > )) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # select this short name and some antiseptic drugs< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > bug< / span > , < span class = 'no' > CXM< / span > , < span class = 'no' > GEN< / span > , < span class = 'no' > CIP< / span > ) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # group by MO< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/group_by.html' > group_by< / a > < / span > (< span class = 'no' > bug< / span > ) < span class = 'kw' > %> %< / span >
2018-12-23 21:26:21 +01:00
< span class = 'co' > # plot the thing, putting MOs on the facet< / span >
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< span class = 'fu' > ggplot_rsi< / span > (< span class = 'kw' > x< / span > < span class = 'kw' > =< / span > < span class = 'st' > "antibiotic"< / span > ,
2019-05-31 20:25:57 +02:00
< span class = 'kw' > facet< / span > < span class = 'kw' > =< / span > < span class = 'st' > "bug"< / span > ,
2018-12-23 21:26:21 +01:00
< span class = 'kw' > translate_ab< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > ,
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< span class = 'kw' > nrow< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 1< / span > ,
< span class = 'kw' > title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "AMR of Top Three Microorganisms In Blood Culture Isolates"< / span > ,
2019-05-31 21:20:16 +02:00
< span class = 'kw' > subtitle< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/expression' > expression< / a > < / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/paste' > paste< / a > < / span > (< span class = 'st' > "Only First Isolates, CoNS grouped according to Becker "< / span > ,
< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/grDevices/topics/plotmath' > italic< / a > < / span > (< span class = 'st' > "et al."< / span > ), < span class = 'st' > " (2014)"< / span > )),
2019-05-31 20:48:22 +02:00
< span class = 'kw' > x.title< / span > < span class = 'kw' > =< / span > < span class = 'st' > "Antibiotic (EARS-Net code)"< / span > )
2019-01-02 23:24:07 +01:00
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2018-12-23 21:26:21 +01:00
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2018-12-29 22:24:19 +01:00
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