Creates a heatmap (tile plot) of indicator values.
It can plot longitudinal data (date-based) or seasonal/categorical data
(factor-based) depending on the input provided to the x argument.
Usage
plot_heatmap(
data,
x = "monyear",
y_var = "state",
fill = "value",
title = NULL,
legend_title = "Value",
palette = c("viridis", "diverging", "sequential")
)Arguments
- data
A data frame, typically from
get_hmis()or a summarized version.- x
Column for x-axis. Default
"monyear". If"monyear"is used, it is automatically parsed to a Date. If a factor (like "month") is provided, the function automatically switches to a discrete scale.- y_var
Column for y-axis. Default
"state".- fill
Column for fill color. Default
"value".- title
Plot title. Default auto-generated.
- legend_title
Legend title. Default
"Value".- palette
One of
"viridis","diverging", or"sequential". Default"viridis".
Examples
if (FALSE) { # \dontrun{
# Standard Longitudinal View (uses scale_x_date)
malaria <- get_hmis("Number of blood smears examined for Malaria",
from = "Apr 2017", to = "Mar 2020"
)
plot_heatmap(malaria)
# Seasonal View (uses scale_x_discrete)
# Assumes 'month' is a factor (Jan-Dec) and 'cal_year' is a column
plot_heatmap(nmr_heat_norm, x = "month", y_var = "cal_year", fill = "nmr_norm")
} # }