cast

This has two consequences:

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).
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.

cast(input: column, {
    "param": value,
    ...
}) -> (output: column)

type

string

default:"number"

Desired semantic type of the converted data. Make data numerical with "type": "number".

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:

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:

Prepare

Analyse

Report