Float#

synthesized.metadata.value.Float

class Float(name, children=None, categories=None, nan_freq=None, num_rows=None, unit_meta=None)#

Methods

`children_from_dict`(d)	rtype `Optional`[`Sequence`[`TypeVar`(`MetaType`, bound= `Meta`, covariant=True)]]
`convert_df_for_children`(df)	Expands the dataframe to contain the columns of the metas children.
`create_index`(df)	rtype `Index`
`extract`(df)	Extract the categories and their relative frequencies from a data frame, if not already set.
`from_dict`(d)	Construct a Meta from a dictionary.
`from_name_and_dict`(class_name, d)	Construct a Meta from a meta class name and a dictionary.
`get`(k[,d])
`get_registry`()	rtype `Dict`[`str`, `Type`[`TypeVar`(`MetaType`, bound= `Meta`, covariant=True)]]
`items`()
`keys`()
`less_than`(x, y)	rtype `bool`
`revert_df_from_children`(df)	Collapses the dataframe to no longer contain the meta's children columns.
`sort`(sr)	Sort pd.Series according to the ordering of this meta
`to_dict`()	Convert the Meta to a dictionary.
`unfold`(df)	rtype `DataFrame`
`update_meta`(df)	Update the categories and nan_freq if required be
`values`()

Attributes

`categories`	rtype `Sequence`[`TypeVar`(`NType`, bound= `Union`[`str`, `bool_`, `datetime64`, `timedelta64`, `int64`, `float64`])]
`children`	Return the children of this Meta.
`class_name`
`dtype`
`max`	rtype `Optional`[`TypeVar`(`OType`, bound= `Union`[`str`, `bool_`, `datetime64`, `timedelta64`, `int64`, `float64`])]
`min`	rtype `Optional`[`TypeVar`(`OType`, bound= `Union`[`str`, `bool_`, `datetime64`, `timedelta64`, `int64`, `float64`])]
`precision`	rtype `TypeVar`(`SType`, bound= `Union`[`timedelta64`, `int64`, `float64`])
`unit_meta`	rtype `Scale`[`Any`]

property children#

Return the children of this Meta.

Return type: Sequence[TypeVar(MetaType, bound= Meta, covariant=True)]

convert_df_for_children(df)#: Expands the dataframe to contain the columns of the metas children.

extract(df)#

Extract the categories and their relative frequencies from a data frame, if not already set.

classmethod from_dict(d)#

Construct a Meta from a dictionary.

See example in Meta.to_dict() for the required structure.

See also

Meta.from_dict: construct a Meta from a dictionary

revert_df_from_children(df)#: Collapses the dataframe to no longer contain the meta’s children columns.

sort(sr)#

Sort pd.Series according to the ordering of this meta

Return type: Sequence[TypeVar(AType, bound= Union[datetime64, timedelta64, int64, float64])]

to_dict()#

Convert the Meta to a dictionary.

The tree structure is converted to the following form:

{
    attr: value,
    children: {
        name: {**value_meta_attr.__dict__}
    }
}