GHRexplore (version 0.2.1)

plot_timeseries2: Time series plot of two variables in two different axes

Description

Plots dual-axis time series of two covariates, case counts, or incidence rates.

Usage

plot_timeseries2(
  data,
  var,
  time,
  type = c("cov", "cov"),
  pop = NULL,
  pt = 1e+05,
  area = NULL,
  aggregate_space = NULL,
  aggregate_time = NULL,
  aggregate_space_fun = "mean",
  aggregate_time_fun = "mean",
  align = "min",
  title = NULL,
  var_label = NULL,
  legend = "Variable",
  ylab = NULL,
  xlab = NULL,
  free_y_scale = FALSE,
  palette = c("#168c81", "#B98AFB"),
  alpha = 0.9
)

Value

A dual-axis ggplot2 time series plot.

Arguments

data

Data frame containing equally spaced (daily, weekly, monthly) covariate or disease case observations for one or multiple locations.

var

A character vector of length 2 (left axis, right axis) identifying the variables to be plotted.

time

Name of the variable that identifies the temporal dimension of the data frame. Its values must be in date format ("yyyy-mm-dd") representing the day of observation for daily data, the first day of the week for weekly, or the first day of the month for monthly observations.

type

A character vector of length 2 (left axis, right axis) that specifies the types of variable in var. Possible values include 'cov' (covariate, default), 'counts' (case counts), and 'inc' (case incidence). If type='inc', pop is required.

pop

Character identifying the variable name for population. Only needed if type='inc'.

pt

Numerical only used for type='inc'. It represents the scale of the person-time (default 100,000) for incidence rates.

area

Name of variable that identifies the different locations (e.g., areal units) for which a time series is available.

aggregate_space

Name of variable used to define spatial aggregation groups.

aggregate_time

Temporal scale used to perform temporal aggregation. Options are: "week" (ISO 8601), "month", "year".

aggregate_space_fun

Character indicating the function to be used in the aggregation over space for type="cov". Options are "mean" (default), "median", "sum". For case counts and incidence, "sum" is always applied.

aggregate_time_fun

Character indicating the function to be used in the aggregation over time for type="cov". Options are "mean" (default), "median", "sum". For case counts and incidence, "sum" is always applied.

align

Options to align the two plots. Defaults to "min", which forces the minimum of the two variables to be aligned. Other options include "mean" and "median".

title

Optional title of the plot.

var_label

A character vector of length 2 (left axis, right axis) with custom names for the case or covariate variable.

legend

Character with a custom name for the legend.

ylab

A character vector of length 2 (left, right) for the y-axes.

xlab

Label for the x-axis.

free_y_scale

Logical, default FALSE. Allows different scales in the y_axis when facets are used.

palette

A character vector of length 2 (left axis, right axis) indicating the colours (R or hex codes) to use for each of the two variables).

alpha

Numerical between 0 and 1 determining the transparency of the lines.

See Also

plot_timeseries for single-axis time series plots.

Examples

# Load data
data("dengue_MS")
data("dengue_SP")

# Plotting two covariates with temporal aggregation, align using the mean
plot_timeseries2(dengue_SP,
                 var = c("temp_med", "precip_tot"),
                 time = "date",
                 align = "mean",
                 aggregate_time = "month")

# Plotting case incidence and a covariate with temporal aggregation 
# and customized colours and labels
plot_timeseries2(dengue_SP,
                 var = c("cases", "precip_tot"),
                 type = c("inc", "cov"),
                 var_label = c("Incidence", "Precipitation"),
                 title = "Precipitation and dengue incidence in Sao Paulo",
                 time = "date",
                 pop = "pop",
                 aggregate_time = "month",
                 palette = c("darkgreen", "royalblue"),
                 alpha = 0.8)
                 
# Plotting case incidence and a covariate with spatial aggregation
plot_timeseries2(dengue_MS,
                 var = c("dengue_cases", "pdsi"),
                 type = c("inc", "cov"),
                 pop = "population",
                 time = "date",
                 area = "micro_code",
                 aggregate_space = "meso_code")