R/bind_line_bar_pie_data.R

In flourishcharts: 'Flourish' for 'R' and 'Python'

#' Bind line, bar and pie charts data
#' @name bind_line_bar_pie_data
#' @param data Data.
#' @param label Labels/time. A column of names, numbers or datetimes. Suggested data type hints: string, datetime, number. Flourish type hint: column
#' @param value Values. One or more columns of numbers. The Preferred output format of the first column is used to format values. Suggested data type hints: number. Flourish type hint: columns
#' @param facet Charts grid. If specified and  Grid of charts  view is on, creates a separate mini chart for each value found in the column. Suggested data type hints: string. Flourish type hint: column
#' @param filter Row filter. Use this column to create a user-facing row control. To create a column filter, use the  Series filter  option in the settings panel instead. Suggested data type hints: string, datetime, number. Flourish type hint: column
#' @param metadata Info for custom popups. One or more columns of information (text,  image URLs ,  embedded charts  etc) to include in custom  popups and panels Suggested data type hints: string, datetime, number. Flourish type hint: columns
#' @param 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).
#' @param 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).
#' @param metadata_input_format Formats/parses dates, strings, and numbers for the metadata column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param metadata_output_format Formats/parses dates, strings, and numbers for the metadata column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param label_input_format Formats/parses dates, strings, and numbers for the label column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param label_output_format Formats/parses dates, strings, and numbers for the label column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param filter_input_format Formats/parses dates, strings, and numbers for the filter column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param filter_output_format Formats/parses dates, strings, and numbers for the filter column. If string: any arbritrary string. 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/](https://developers.flourish.studio/api/create-visualisation/).. 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).
#' @param 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).
#' @param 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).
#' @param . 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).
#' @return A Flourish chart
#' @examples 
#' try(
#'   flourish(chart_type = "line", api_key = Sys.getenv("FLOURISH_API_KEY")) |> 
#'   bind_line_bar_pie_data(gapminder)
#' )
#' @export


bind_line_bar_pie_data <- function(
    .,
    data = NULL,
    label = NULL,
    value = NULL,
    facet = NULL,
    filter = NULL,
    metadata = NULL,
    facet_input_format = NULL,
    facet_output_format = NULL,
    metadata_input_format = NULL,
    metadata_output_format = NULL,
    label_input_format = NULL,
    label_output_format = NULL,
    filter_input_format = NULL,
    filter_output_format = NULL,
    value_input_format = NULL,
    value_output_format = NULL) {
  bindings_error(., "line_bar_pie")

  old_list <- .
  new_list <- list()

  if (!is.null(data)) {
    columns_data <- c(paste(label), paste(value), paste(facet), paste(filter), paste(metadata), NULL)
    columns_data <- columns_data[!sapply(columns_data, is.null)]
    spelling_check_column_names(
      strings = strsplit(columns_data, split = ",", fixed = TRUE),
      data = data
    )
    int_columns_data <- sapply(data, is.integer)
    data[, int_columns_data] <- lapply(data[, int_columns_data], as.character)
  }
  new_list$x$data$data <- data
  new_list$x$bindings$data$label <- label

  if (is.null(value)) {
    new_list$x$bindings$data$value <- "list"
  } else {
    new_list$x$bindings$data$value <- value
  }

  new_list$x$bindings$data$facet <- facet
  new_list$x$bindings$data$filter <- filter

  if (is.null(metadata)) {
    new_list$x$bindings$data$metadata <- "list"
  } else {
    new_list$x$bindings$data$metadata <- metadata
  }



  if (!is.null(label_output_format) && !is.null(label_input_format)) {
    if (isTRUE(grepl("^%", label_output_format))) {
      new_list$x$metadata$data$label$type <- "datetime"
      new_list$x$metadata$data$label$type_id <- paste0("datetime$", label_input_format)
      new_list$x$metadata$data$label$output_format_id <- paste0("datetime$", label_output_format)
    } else if (isTRUE(grepl("_", label_output_format))) {
      new_list$x$metadata$data$label$type <- "number"
      new_list$x$metadata$data$label$type_id <- paste0("number$", label_input_format)
      new_list$x$metadata$data$label$output_format_id <- paste0("number$", label_output_format)
    } else if (isTRUE(!is.na(label_output_format) && isFALSE(grepl("_", label_output_format)) && isFALSE(grepl("^%", label_output_format)))) {
      new_list$x$metadata$data$label$type <- "string"
      new_list$x$metadata$data$label$type_id <- paste0("string$", label_input_format)
      new_list$x$metadata$data$label$output_format_id <- paste0("string$", label_output_format)
    }
    if (is.na(label_input_format) && !is.na(label_output_format)) {
      "[label_input_format] and [label_output_format] must both be defined."
    }
    if (!is.na(label_input_format) && is.na(label_output_format)) {
      "[label_input_format] and [label_output_format] must both be defined."
    }
  }


  if (!is.null(value_output_format) && !is.null(value_input_format)) {
    if (isTRUE(grepl("^%", value_output_format))) {
      new_list$x$metadata$data$value$type <- "datetime"
      new_list$x$metadata$data$value$type_id <- paste0("datetime$", value_input_format)
      new_list$x$metadata$data$value$output_format_id <- paste0("datetime$", value_output_format)
    } else if (isTRUE(grepl("_", value_output_format))) {
      new_list$x$metadata$data$value$type <- "number"
      new_list$x$metadata$data$value$type_id <- paste0("number$", value_input_format)
      new_list$x$metadata$data$value$output_format_id <- paste0("number$", value_output_format)
    } else if (isTRUE(!is.na(value_output_format) && isFALSE(grepl("_", value_output_format)) && isFALSE(grepl("^%", value_output_format)))) {
      new_list$x$metadata$data$value$type <- "string"
      new_list$x$metadata$data$value$type_id <- paste0("string$", value_input_format)
      new_list$x$metadata$data$value$output_format_id <- paste0("string$", value_output_format)
    }
    if (is.na(value_input_format) && !is.na(value_output_format)) {
      "[value_input_format] and [value_output_format] must both be defined."
    }
    if (!is.na(value_input_format) && is.na(value_output_format)) {
      "[value_input_format] and [value_output_format] must both be defined."
    }
  }


  if (!is.null(facet_output_format) && !is.null(facet_input_format)) {
    if (isTRUE(grepl("^%", facet_output_format))) {
      new_list$x$metadata$data$facet$type <- "datetime"
      new_list$x$metadata$data$facet$type_id <- paste0("datetime$", facet_input_format)
      new_list$x$metadata$data$facet$output_format_id <- paste0("datetime$", facet_output_format)
    } else if (isTRUE(grepl("_", facet_output_format))) {
      new_list$x$metadata$data$facet$type <- "number"
      new_list$x$metadata$data$facet$type_id <- paste0("number$", facet_input_format)
      new_list$x$metadata$data$facet$output_format_id <- paste0("number$", facet_output_format)
    } else if (isTRUE(!is.na(facet_output_format) && isFALSE(grepl("_", facet_output_format)) && isFALSE(grepl("^%", facet_output_format)))) {
      new_list$x$metadata$data$facet$type <- "string"
      new_list$x$metadata$data$facet$type_id <- paste0("string$", facet_input_format)
      new_list$x$metadata$data$facet$output_format_id <- paste0("string$", facet_output_format)
    }
    if (is.na(facet_input_format) && !is.na(facet_output_format)) {
      "[facet_input_format] and [facet_output_format] must both be defined."
    }
    if (!is.na(facet_input_format) && is.na(facet_output_format)) {
      "[facet_input_format] and [facet_output_format] must both be defined."
    }
  }


  if (!is.null(filter_output_format) && !is.null(filter_input_format)) {
    if (isTRUE(grepl("^%", filter_output_format))) {
      new_list$x$metadata$data$filter$type <- "datetime"
      new_list$x$metadata$data$filter$type_id <- paste0("datetime$", filter_input_format)
      new_list$x$metadata$data$filter$output_format_id <- paste0("datetime$", filter_output_format)
    } else if (isTRUE(grepl("_", filter_output_format))) {
      new_list$x$metadata$data$filter$type <- "number"
      new_list$x$metadata$data$filter$type_id <- paste0("number$", filter_input_format)
      new_list$x$metadata$data$filter$output_format_id <- paste0("number$", filter_output_format)
    } else if (isTRUE(!is.na(filter_output_format) && isFALSE(grepl("_", filter_output_format)) && isFALSE(grepl("^%", filter_output_format)))) {
      new_list$x$metadata$data$filter$type <- "string"
      new_list$x$metadata$data$filter$type_id <- paste0("string$", filter_input_format)
      new_list$x$metadata$data$filter$output_format_id <- paste0("string$", filter_output_format)
    }
    if (is.na(filter_input_format) && !is.na(filter_output_format)) {
      "[filter_input_format] and [filter_output_format] must both be defined."
    }
    if (!is.na(filter_input_format) && is.na(filter_output_format)) {
      "[filter_input_format] and [filter_output_format] must both be defined."
    }
  }


  if (!is.null(metadata_output_format) && !is.null(metadata_input_format)) {
    if (isTRUE(grepl("^%", metadata_output_format))) {
      new_list$x$metadata$data$metadata$type <- "datetime"
      new_list$x$metadata$data$metadata$type_id <- paste0("datetime$", metadata_input_format)
      new_list$x$metadata$data$metadata$output_format_id <- paste0("datetime$", metadata_output_format)
    } else if (isTRUE(grepl("_", metadata_output_format))) {
      new_list$x$metadata$data$metadata$type <- "number"
      new_list$x$metadata$data$metadata$type_id <- paste0("number$", metadata_input_format)
      new_list$x$metadata$data$metadata$output_format_id <- paste0("number$", metadata_output_format)
    } else if (isTRUE(!is.na(metadata_output_format) && isFALSE(grepl("_", metadata_output_format)) && isFALSE(grepl("^%", metadata_output_format)))) {
      new_list$x$metadata$data$metadata$type <- "string"
      new_list$x$metadata$data$metadata$type_id <- paste0("string$", metadata_input_format)
      new_list$x$metadata$data$metadata$output_format_id <- paste0("string$", metadata_output_format)
    }
    if (is.na(metadata_input_format) && !is.na(metadata_output_format)) {
      "[metadata_input_format] and [metadata_output_format] must both be defined."
    }
    if (!is.na(metadata_input_format) && is.na(metadata_output_format)) {
      "[metadata_input_format] and [metadata_output_format] must both be defined."
    }
  }
  deep_merge(old_list, new_list)
}