Plot measures of TB burden by country by specifying a metric from the TB burden data. Specify a country or vector of countries in order to plot them (by default plots all countries). Various other options are available for tuning the plot further.
plot_tb_burden(
df = NULL,
dict = NULL,
metric = "e_inc_100k",
metric_label = NULL,
smooth = FALSE,
conf = c("_lo", "_hi"),
countries = NULL,
years = NULL,
compare_to_region = FALSE,
facet = NULL,
legend = "none",
annual_change = FALSE,
trans = "identity",
scales = "fixed",
interactive = FALSE,
download_data = TRUE,
save = TRUE,
viridis_palette = "viridis",
viridis_direction = -1,
viridis_end = 0.9,
verbose = FALSE,
...
)
Dataframe of TB burden data, as sourced by get_tb_burden
.
If not specified then will source the WHO TB burden data, either locally if available
or directly from the WHO (if download_data = TRUE
).
A tibble of the data dictionary. See get_data_dict
for details. If not supplied the function will attempt to load a saved version of the
dictionary. If this fails and download_data = TRUE
then the dictionary will be downloaded.
Character string specifying the metric to plot
Character string specifying the metric label to use.
Logical, defaults to FALSE
. Should the data be smoothed (using ggplot2::geom_smooth
)
prior to plotting. If set to TRUE
then the confidence intervals shown are derived from the smooth
and do not represent the underlying uncertainty in the data.
Character vector specifying the name variations to use to specify the upper
and lower confidence intervals. Defaults to c("_lo", "_hi"), if set to NULL
then no confidence intervals are shown. When annual_change = TRUE
the confidence
intervals represent the annual percentage change in the metrics confidence intervals.
A character string specifying the countries to target.
Numeric vector of years. Defaults to NULL
which includes all years in the data.
Logical, defaults to FALSE
. If TRUE
all
countries that share a region with those listed in countries
will be plotted.
Note that this will override settings for facet
, unless it is set to "country".
Character string, the name of the variable to facet by.
Character string, defaults to "none"
. Position of the legend see ?ggplot2::theme
for defaults but known
options are: "none"
, "top"
, "right"
and "bottom"
.
Logical, defaults to FALSE
. If TRUE
then the
percentage annual change is computed for the specified metric.
A character string specifying the transform to use on the specified metric. Defaults to no
transform ("identity"). Other options include log scaling ("log") and log base 10 scaling
("log10"). For a complete list of options see ggplot2::continous_scale
.
Character string, see ?ggplot2::facet_wrap for details. Defaults to "fixed", alternatives are "free_y", "free_x", or "free".
Logical, defaults to FALSE
. If TRUE
then an interactive plot is
returned.
Logical, defaults to TRUE
. If not found locally should the data be
downloaded from the specified URL?
Logical, should the data be saved for reuse during the current R session. Defaults to
TRUE
. If TRUE
then the data is saved to the temporary directory specified by tempdir
.
Character string indicating the viridis
colour palette to use. Defaults
to "viridis". Options include "cividis", "magma", "inferno", "plasma", and "viridis". For additional details
see viridis_pal
for additional details.
Numeric, indicating the direction for the colour palette (1 or -1), defaults to -1.
See scale_color_viridis
for additional details.
Numeric between 0 and 1, defaults to 0.9. The end point of the viridis scale to use.
#' See scale_color_viridis
for additional details.
Logical, defaults to FALSE
. Should additional status and progress messages
be displayed.
Additional arguments to pass to get_tb_burden
.
A plot of TB Incidence Rates by Country
get_tb_burden search_data_dict
# NOT RUN {
## Get the WHO TB burden data and the data dictionary
tb_burden <- get_tb_burden()
dict <- get_data_dict()
## Get a random sample of 9 countries
sample_countries <- sample(unique(tb_burden$country), 9)
## Plot incidence rates in these countries
plot_tb_burden(df = tb_burden, dict = dict, facet = "country", countries = sample_countries)
# }
# NOT RUN {
## Plot smoothed incidence rates in these countries
plot_tb_burden(
df = tb_burden, dict = dict, facet = "country", smooth = TRUE,
countries = sample_countries
)
## Use data caching to plot incidence rates with free y scales
plot_tb_burden(facet = "country", countries = sample_countries, scales = "free_y")
## Plot annual percentage change in incidence rates in selected countries
plot_tb_burden(
df = tb_burden, dict = dict, facet = "country", scales = "free_y",
countries = sample_countries, annual_change = TRUE, conf = NULL
)
## Find variables relating to mortality in the WHO dataset
search_data_dict(def = "mortality")
## Plot mortality rates (exc HIV) - without progress messages
plot_tb_burden(
metric = "e_mort_exc_tbhiv_100k", facet = "country",
countries = sample_countries, scales = "free_y"
)
# }
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