View source: R/visualize_pathways_level2.R
visualize_pathways_level2 | R Documentation |
Function to plot bar graph with number of taxa introduced by different pathways at level 2, given a pathway level 1. Possible breakpoints: taxonomic (kingdoms + vertebrates/invertebrates) and temporal (lower limit year).
visualize_pathways_level2(
df,
chosen_pathway_level1,
category = NULL,
from = NULL,
facet_column = NULL,
pathways = NULL,
pathway_level1_names = "pathway_level1",
pathway_level2_names = "pathway_level2",
taxon_names = "key",
kingdom_names = "kingdom",
phylum_names = "phylum",
first_observed = "first_observed",
cbd_standard = TRUE,
title = NULL,
x_lab = "Number of introduced taxa",
y_lab = "Pathways"
)
df |
df. |
chosen_pathway_level1 |
character. A pathway level 1. If CBD standard is
followed (see argument |
category |
|
from |
|
facet_column |
|
pathways |
character. Vector with pathways level 2 to visualize. The pathways are displayed following the order as in this vector. |
pathway_level1_names |
character. Name of the column of |
pathway_level2_names |
character. Name of the column of |
taxon_names |
character. Name of the column of |
kingdom_names |
character. Name of the column of |
phylum_names |
character. Name of the column of |
first_observed |
character. Name of the column of |
cbd_standard |
logical. If |
title |
|
x_lab |
|
y_lab |
|
A list with three slots:
plot
: ggplot2 object (or egg object if facets are used). NULL
if there
are no data to plot.
data_top_graph
: data.frame (tibble) with data used for the main plot (top
graph) in plot
.
data_facet_graph
: data.frame (tibble) with data used for the faceting
plot in plot
. NULL
is returned if facet_column
is NULL
.
## Not run:
library(readr)
datafile <- paste0(
"https://raw.githubusercontent.com/trias-project/indicators/master/data/",
"interim/data_input_checklist_indicators.tsv"
)
data <- read_tsv(datafile,
na = "",
col_types = cols(
.default = col_character(),
key = col_double(),
nubKey = col_double(),
speciesKey = col_double(),
first_observed = col_double(),
last_observed = col_double()
)
)
# All taxa
visualize_pathways_level2(data, chosen_pathway_level1 = "escape")
# Animalia
visualize_pathways_level2(data,
chosen_pathway_level1 = "escape",
category = "Animalia"
)
# Chordata
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
category = "Chordata"
)
# select some pathways only
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
pathways = c("pet", "horticulture")
)
# facet phylum
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
category = "Animalia",
facet_column = "phylum"
)
# facet habitat
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
facet_column = "habitat"
)
# Only taxa introduced from 1950
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
from = 1950
)
# Add a title
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
category = "Plantae",
from = 1950,
title = "Pathway level 2 (escape): Plantae, from 1950"
)
# Personalize axis labels
visualize_pathways_level2(
df = data,
chosen_pathway_level1 = "escape",
x_lab = "Aantal taxa",
y_lab = "pathways"
)
## End(Not run)
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