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This has two consequences:
  1. It will allow the resulting column to be used by steps only accepting the new type, e.g. when casting a column of concatenated texts to the "url" type, so that it may be used where Urls are expected (e.g. the step fetch_url_content).
  2. It will change any values not conformant with the new type to the missing value (NaN). E.g., casting a column of mixed data containing numbers to the "number" type, will replace all values that cannot be read as numbers with NaN.
Note that for each possible type a column can be cast to (via the "type" parameter, e.g. "number", "category" etc.), the steps accepts different configuration parameters. See the subsections under Parameters below for further details.

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Usage

The following example shows how the step can be used in a recipe.

Examples

  • Example 1
  • Signature
E.g. to simply convert a text column to a category column, use:
cast(ds.text, {"type": "category"}) -> (ds.new_cat)

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Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").
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input
column
required
The column you wish to cast.
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output
column
required
A new column with original data cast to the desired type.

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Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).

Parameters

  • number
  • list[number]
  • currency
  • list[currency]
  • date
  • list[date]
  • text
  • category
  • list[category]
  • url
  • list[url]
  • sex
  • list[sex]
  • boolean
  • list[boolean]
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type
string
default:"number"
Desired semantic type of the converted data. Make data numerical with "type": "number".
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decimal
string
default:"."
Separator to mark the decimal part. Use ”.” or ”,” to indicate how decimal values are separated when parsing text strings into numerical format. It is automatically assumed that the other character is used as the thousands separator. E.g. "decimal": "." assumes that the period ”.” is used to separate decimals and ”,” thousands, as in the number string “12,173.12”.Values must be one of the following:
  • .
  • ,
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thousand
string
default:","
Separator to mark the thousands. Use ”.” or ”,” to indicate how thousands are separated when parsing text strings into numerical format. It is automatically assumed that the other character is used as the decimal separator. E.g. "thousand": "." assumes that the period ”.” is used to separate thousands and ”,” decimals, as in the number string “12.173,12”.Values must be one of the following:
  • .
  • ,
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