pointblank (version 0.7.0)

yaml_read_informant: Read a pointblank YAML file to create an informant object

Description

With yaml_read_informant() we can read a pointblank YAML file that describes table information (typically generated by the yaml_write() function. What's returned is a new informant object with the information intact. The informant object can be given more information through use of the info_*() functions.

Usage

yaml_read_informant(filename, path = NULL)

Arguments

filename

The name of the YAML file that contains fields related to an informant.

path

An optional path to the YAML file (combined with filename).

Function ID

11-3

See Also

Other pointblank YAML: yaml_agent_interrogate(), yaml_agent_show_exprs(), yaml_agent_string(), yaml_exec(), yaml_informant_incorporate(), yaml_read_agent(), yaml_write()

Examples

# NOT RUN {
if (interactive()) {

# Create a pointblank `informant`
# object with `create_informant()`
# and the `small_table` dataset
informant <- create_informant(small_table)

# An `informant` object can be written
# to a YAML file with the `yaml_write()`
# function
# yaml_write(
#   informant = informant,
#   filename = "informant-small_table.yml"
# )

# The `informant-small_table.yml` file
# looks like this when written

#> info_label: '[2020-09-06|13:37:38]'
#> table:
#>   name: small_table
#> _columns: 8
#> _rows: 13
#> _type: tbl_df
#> columns:
#>   date_time:
#>     _type: POSIXct, POSIXt
#>   date:
#>     _type: Date
#>   a:
#>     _type: integer
#>   b:
#>     _type: character
#>   c:
#>     _type: numeric
#>   d:
#>     _type: numeric
#>   e:
#>     _type: logical
#>   f:
#>     _type: character

# We can add keys and values to
# add more pertinent information; with
# some direct editing of the file we get:

#> info_label: '[2020-09-06|13:37:38]'
#> table:
#>   name: small_table
#>   _columns: 8
#>   _rows: 13
#>   _type: tbl_df
#> columns:
#>   date_time:
#>     _type: POSIXct, POSIXt
#>     info: Date-time values.
#>   date:
#>     _type: Date
#>     info: Date values (the date part of `date_time`).
#>   a:
#>     _type: integer
#>     info: Small integer values (no missing values).
#>   b:
#>     _type: character
#>     info: Strings with a common pattern.
#>   c:
#>     _type: numeric
#>     info: Small numeric values (contains missing values).
#>   d:
#>     _type: numeric
#>     info: Large numeric values (much greater than `c`).
#>   e:
#>     _type: logical
#>     info: TRUE and FALSE values.
#>   f:
#>     _type: character
#>     info: Strings of the set `"low"`, `"mid"`, and `"high"`.

# We could also have done the same
# with the `informant` object by use of
# the `info_columns()` function

# The 'informant-small_table.yml' file
# is available in the package through
# `system.file()`
yml_file <- 
  system.file(
    "yaml", "informant-small_table.yml",
    package = "pointblank"
  )

# We can read this YAML file back
# as an `informant` object by using
# `yaml_read_informant()`
informant <- 
  yaml_read_informant(filename = yml_file)

class(informant)

}

# }