plot_sites: Plot sites on US map
| plot_sites | R Documentation |
Plot sites on US map
Description
Plot sites on US map
Usage
plot_sites(
data,
id = NA_character_,
alpha = 1,
labels = TRUE,
color_var = "package_id",
shape_var = "package_id"
)
Arguments
data |
(list or tbl_df, tbl, data.frame) The dataset object returned by |
id |
(character) Identifier of dataset to be used in plot subtitles. Is automatically assigned when |
alpha |
(numeric) Alpha-transparency scale of data points. Useful when many data points overlap. Allowed values are between 0 and 1, where 1 is 100% opaque. Default is 1. |
labels |
(logical) Argument to show labels of each US state. Default is TRUE. |
color_var |
(character) Name of column to use to assign colors to the points on the plot |
shape_var |
(character) Name of column to use to assign shapes to the points on the plot |
Details
The data parameter accepts a range of input types but ultimately requires the 14 columns of the combined observation and location tables.
Value
(gg, ggplot) A gg, ggplot object if assigned to a variable, otherwise a plot to your active graphics device
Examples
## Not run:
library(dplyr)
# Read a dataset of interest
dataset <- read_data("edi.193.5")
# Plot the dataset
plot_sites(dataset)
# Flatten dataset then plot
dataset %>%
flatten_data() %>%
plot_sites()
# Download a NEON dataset
dataset2 <- read_data(
id = "neon.ecocomdp.20120.001.001",
site= c('COMO','LECO'),
startdate = "2017-06",
enddate = "2021-03",
token = Sys.getenv("NEON_TOKEN"), # option to use a NEON token
check.size = FALSE)
# Combine the two datasets and plot. This requires the datasets be first
# flattened and then stacked.
flattened_data1 <- dataset %>% flatten_data()
flattened_data2 <- dataset2 %>% flatten_data()
stacked_data <- bind_rows(flattened_data1,flattened_data2)
plot_sites(stacked_data)
## End(Not run)
# Plot the example dataset
plot_sites(ants_L1)
