summarizeNWS | R Documentation |
Summarize spatial data using a polygon layer to return raw values for each date and aggregate measures by month.
summarizeNWS(
tif_addresses,
parameter = "observed",
input_polygon,
polygon_names = NULL,
create_plots = FALSE,
func = mean,
date_correction = -1
)
tif_addresses |
character vector with full file names for tiff files to be summarized (including entire directory and file extension). Can be created with ‘list.files(’C:/directory', full.names = TRUE)'. |
parameter |
character element used to select the appropriate data layers. Acceptable 'parameter' values include 'observed', 'normal', 'departure_in', and 'departure_pct'. |
input_polygon |
Spatvector with polygons used to summarize precipitation data. Load with 'terra::vect'. Example polygon data: https://catalog.data.gov/dataset/tiger-line-shapefile-2019-state-georgia-current-county-subdivision-state-based |
polygon_names |
character. Name of column in 'input_polygon' containing feature names/IDs. If left as 'NULL', features are numbered by their row in the polygon object. |
create_plots |
logical. Optional visualization produced for each layer. Setting this to 'TRUE' will dramatically slow down the run time. |
func |
function. Used to summarize the monthly data from each polygon. |
date_correction |
numeric. Optional correction for data date. For example, setting this to ‘-1' could be appropriate for a layer dated February 1st that captures January’s monthly precipitation totals. If no correction is desired, set to 0. |
list summarizeNWS
containing (1) 'summary_table', a summary dataframe showing the result of 'func' applied to monthly values for Jan-Dec. More complex operations can be performed on the raw values, and (2) 'all_data', a dataframe containing the raw values from each polygon and each layer.
2+2
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.