bind_sankey_data: Bind sankey diagram data

Description

Bind sankey diagram data

Usage

bind_sankey_data(
  .,
  data = NULL,
  source = NULL,
  target = NULL,
  value = NULL,
  filter = NULL,
  facet = NULL,
  step_from = NULL,
  step_to = NULL,
  metadata = NULL,
  filter_input_format = NULL,
  filter_output_format = NULL,
  facet_input_format = NULL,
  facet_output_format = NULL,
  metadata_input_format = NULL,
  metadata_output_format = NULL,
  source_input_format = NULL,
  source_output_format = NULL,
  step_from_input_format = NULL,
  step_from_output_format = NULL,
  step_to_input_format = NULL,
  step_to_output_format = NULL,
  target_input_format = NULL,
  target_output_format = NULL,
  value_input_format = NULL,
  value_output_format = NULL
)

Value

A Flourish chart

Arguments

.: The prior Flourish object. No need to specify name if piping graph as the graph will take the first argument (i.e. the prior existing graph).
data: Data.
source: Source. Suggested data type hints: string. Flourish type hint: column
target: Target. Suggested data type hints: string. Flourish type hint: column
value: Value of link. A numerical value used to set the thickness of the links. Suggested data type hints: number. Flourish type hint: column
filter: Filter. Suggested data type hints: string, number, datetime. Flourish type hint: column
facet: Grid of charts. Suggested data type hints: string. Flourish type hint: column
step_from: Step from. An integer(whole number) used to indicate where a link starts from (used only in Alluvial mode). Suggested data type hints: number. Flourish type hint: column
step_to: Step to. An integer(whole number) used to indicate where a link goes to (used only in Alluvial mode). Suggested data type hints: number. Flourish type hint: column
metadata: Info for popups. One or more columns of information (text, image URLs, embedded charts etc) to include in popups and panels Suggested data type hints: number, datetime, string. Flourish type hint: columns
filter_input_format: Formats/parses dates, strings, and numbers for the filter column. If string: any arbritrary string. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. If date-time: A date-time format such as "%Y-%m-%dT%H:%M:%S.%LZ", "%d/%m/%Y", "%d %b", "%-I%p", "Q%q %Y", "%Y Q%q", and so on. All available formats noted in Flourish documentation: https://developers.flourish.studio/api/create-visualisation/.. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
filter_output_format: Formats/parses dates, strings, and numbers for the filter column. If string: any arbritrary string. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. If date-time: A date-time format such as "%Y-%m-%dT%H:%M:%S.%LZ", "%d/%m/%Y", "%d %b", "%-I%p", "Q%q %Y", "%Y Q%q", and so on. All available formats noted in Flourish documentation: https://developers.flourish.studio/api/create-visualisation/.. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
facet_input_format: Formats/parses dates, strings, and numbers for the facet column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
facet_output_format: Formats/parses dates, strings, and numbers for the facet column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
metadata_input_format: Formats/parses dates, strings, and numbers for the metadata column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. If date-time: A date-time format such as "%Y-%m-%dT%H:%M:%S.%LZ", "%d/%m/%Y", "%d %b", "%-I%p", "Q%q %Y", "%Y Q%q", and so on. All available formats noted in Flourish documentation: https://developers.flourish.studio/api/create-visualisation/.. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
metadata_output_format: Formats/parses dates, strings, and numbers for the metadata column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. If date-time: A date-time format such as "%Y-%m-%dT%H:%M:%S.%LZ", "%d/%m/%Y", "%d %b", "%-I%p", "Q%q %Y", "%Y Q%q", and so on. All available formats noted in Flourish documentation: https://developers.flourish.studio/api/create-visualisation/.. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
source_input_format: Formats/parses dates, strings, and numbers for the source column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
source_output_format: Formats/parses dates, strings, and numbers for the source column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
step_from_input_format: Formats/parses dates, strings, and numbers for the step_from column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
step_from_output_format: Formats/parses dates, strings, and numbers for the step_from column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
step_to_input_format: Formats/parses dates, strings, and numbers for the step_to column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
step_to_output_format: Formats/parses dates, strings, and numbers for the step_to column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
target_input_format: Formats/parses dates, strings, and numbers for the target column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
target_output_format: Formats/parses dates, strings, and numbers for the target column. If string: any arbritrary string. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
value_input_format: Formats/parses dates, strings, and numbers for the value column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).
value_output_format: Formats/parses dates, strings, and numbers for the value column. If number: 'comma_point', 'space_point', 'point_comma', 'space_comma', 'none_point', 'none_comma'. Note: column metadata is optional, and the API will interpret your data for you if you do not specify it. A typical example of when specifying metadata can be useful is when column(s) in your data contain numbers or dates that you wish to format visually (e.g. to display a column containing MM/DD/YYYY dates in DD/MM/YYYY format).

Examples

Run this code

try(
  flourish(chart_type = "sankey", api_key = Sys.getenv("FLOURISH_API_KEY")) |> 
  bind_sankey_data(gapminder)
)

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