quickSource: Quickly Creating BigML Sources
In bigml: Bindings for the BigML API

Description Usage Arguments Details Value Note Author(s) References See Also

Quickly Creating BigML Sources

quickSource(data, name = deparse(substitute(data)),
  header = !is.null(names(data)), locale = "en-US",
  missing_tokens = c("NA"),
  quote = "\"", trim = TRUE, flatten = TRUE, ...)

`data`	A matrix or data frame containing data to upload to bigml.
`name`	A string giving the name of the source.
`header`	A logical value indicating whether to use the first row of data as a header row.
`locale`	A string indicating the desired locale.
`missing_tokens`	A vector listing strings that should be treated as missing.
`quote`	A string giving the quote character to use.
`trim`	A logical value indicating whether to trim white space.
`flatten`	A logical value indicating whether to flatten the response into a data frame.
`...`	Arbitrary named arguments that are passed on to `formEncodeURL` in order to create form-encoded URL options.

quickSource will take its "data" dataframe argument and attempt to create an equivalent BigML source. It does this by converting the dataframe to a csv file, compressing it, and uploading it directly to BigML. Generally, it's better to use quickDataset, since this method attempts to preserve any type information in the data frame.

`category`	numeric
`code`	numeric
`content_type`	character
`created`	character
`credits`	numeric
`description`	character
`fields`	data.frame (or list if flatten=FALSE)
`file_name`	character
`md5`	character
`name`	character
`number_of_datasets`	numeric
`number_of_models`	numeric
`number_of_predictions`	numeric
`private`	logical
`resource`	character
`size`	numeric
`source_parser`	list
`status`	list
`tags`	AsIs
`type`	numeric
`updated`	character