Symbols
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Symbols

Name Private Creator Description
descriptor NO floriandietz@elody.com General-purpose tag to apply a short description to an object in the comment. Intended to help identify objects.
handled NO floriandietz@elody.com General-purpose tag to mark a Tag as 'handled'. What exactly this means depends on the context and should be described by the targeted Tag.
program_was_used_for_this_already NO floriandietz@elody.com This Tag is used to indicate that a Program has already been used for a specific purpose. Details vary by usage.
please_stop_helping NO floriandietz@elody.com This Symbol is used to facilitate cooperation between contributors. It indicates to a Rule or Program that it should skip a certain feature. This is useful e.g. if your program does several things, and one of those is being done better by other programs. This way you can indicate to the program that its help in that area is not required, but you can still benefit from its other features.
info_table_column_count NO floriandietz@elody.com The weight of this Tag describes the number of columns of a table. Arguments of this Tag: 0 : Some object that represents a table, e.g. a file or a [[symbol:modifiable_file]].
rejected NO floriandietz@elody.com General-purpose tag to mark a Tag as 'rejected'. What exactly this means depends on the context and should be described by the targeted Tag.
accepted NO floriandietz@elody.com General-purpose tag to mark a Tag as 'accepted'. What exactly this means depends on the context and should be described by the targeted Tag.
confirmed NO floriandietz@elody.com General-purpose tag to mark a Tag as 'confirmed'. What exactly this means depends on the context and should be described by the targeted Tag.
info_column_nulls_count NO floriandietz@elody.com The weight of this Tag counts the number of null values of a column. This counts only values that are actually missing, i.e. null/None/NaN. It does not count values that are intended as placeholders, such as an empty string. Such placeholders should be converted into null values when necessary. Arguments of this Tag: 0 : A [[symbol:column]] Tag.
info_column_types NO floriandietz@elody.com The comment of this Tag describes the datatype of a column. Valid values are: -primitive values like int32, int64, float32, float64, boolean, string, datetime, ... -special values: daily_date and daily_delta. Both of these are more specific variants of datetime and timedelta, where all values are full days (the hours, minutes, etc. are all 0). -categorical: Different values represent different categories. -numeric: Values can be ordered. -discrete: Values are numeric and there is a finite number of values between any two values. -continuous: Values are numeric and there can be an infinite number of values between two values. -primary_key: A different value for every entry and no null entries. The purpose of this Tag is to inform other Rules and Programs so that they can make intelligent decision. Therefore, being useful is more important than being correct. An integer indicator variable that only has the value 0 and 1, for example, is technically numeric and discrete, but it may make more sense to mark it as categorical instead. The same is true for IDs and for other kinds of numeric values that fall into a suspiciously small number of clusters of different values. If multiple datatypes apply, separate them with commas. Add both leading and trailing commas to make search easier and safer by avoiding accidental prefix/postfix matches. Examples: -The name of the customer: ",string,categorical," -the ID of the item the customer bought: ",primary_key,int64,int,categorical," -The date and time on which an item was bought: ",datetime,continuous,numeric," -The date on which the item is due (without a time component): ",daily_date,datetime,discrete,numeric," -The number of items the customer bought: ",int64,int,discrete,numeric," -The price the customer paid: ",float64,float,continuous,numeric," -The discount of the item: ",float64,float,continuous,numeric,categorical," Note the last example: If the discount is a number, but there are only a fixed number of different discount values, it can be useful both as a numeric value and as a categorical value, depending on the algorithm you want to use. Note that the datatype of the column should be flexible enough to allow all ways of treating the column specified by this Tag. For example, if we are dealing with a Pandas DataFrame and a column is marked as both numeric and categorical, then the column in the Pandas DataFrame should not be of type 'category' as that would make numeric operations impossible. Special case: The comment can be set to "TBD" (for to-be-determined) to indicate that this value needs to be redetermined. This is useful if a program alters the column but does not know how to describe the datatype. It leaves making that description up to other programs. Arguments of this Tag: 0 : A [[symbol:column]] Tag.