Class NormalizationSet manage the Normalizations metadata as OrderedDict supporting Normalizer Class methods and actions. More...

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Public Member Functions
def	__init__ (self)
	The constructor Generate an empty NormalizationSet class with all elements initialized to correct types.

def	reset (self)
	Method oriented to reset a NormalizationSet instance. More...

def	set_base (self, datetime=True)
	Method oriented to establish base Normalization [Metadata]. More...

def	set_ignore_column (self)
	Method oriented to establish ignore_column Normalization [Metadata]. More...

def	set_stdmean (self, mean=0, std=1)
	Method oriented to establish stdmean Normalization [Metadata]. More...

def	set_drop_missing (self)
	Method oriented to establish drop_missing Normalization [Metadata]. More...

def	set_discretize (self, buckets_number=10, fixed_size=True)
	Method oriented to establish bucketing actions [Metadata]. More...

def	set_working_range (self, minval=-1.0, maxval=1.0, minrange=-1.0, maxrange=1.0)
	Method oriented to establish re-scaling data actions [Metadata]. More...

def	set_offset (self, offset=0)
	Method oriented to establish offset (+ or -) data actions [Metadata]. More...

def	set_aggregation (self, bucket_ratio=0.25)
	Method oriented to aggregate minimal and maximal non-frequent values on aggregated intervals [Metadata] Not implemented on Normalizer class [Not Use]. More...

def	set_fixed_missing_values (self, value=0.0)
	Method oriented to establish fixed value imputation data actions into missing values [Metadata]. More...

def	set_mean_missing_values (self, objective_column, full=False)
	Method oriented to establish variable value imputation data actions into missing values based on objective column [Metadata]. More...

def	set_progressive_missing_values (self, objective_column)
	Method oriented to establish variable extrapolated value imputation data actions into missing values based on objective column [Metadata]. More...

Detailed Description

Class NormalizationSet manage the Normalizations metadata as OrderedDict supporting Normalizer Class methods and actions.

Definition at line 17 of file normalizationset.py.

Member Function Documentation

◆ reset()

def gdayf.common.normalizationset.NormalizationSet.reset ( self )

Method oriented to reset a NormalizationSet instance.

Parameters

self	object pointer

Definition at line 27 of file normalizationset.py.

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◆ set_aggregation()

def gdayf.common.normalizationset.NormalizationSet.set_aggregation	(	self,
		bucket_ratio = `0.25`
	)

Method oriented to aggregate minimal and maximal non-frequent values on aggregated intervals [Metadata] Not implemented on Normalizer class [Not Use].

Parameters

self	object pointer
bucket_ratio	ratio for aggregation ratio based on distribution (0.25 means 12.5% minimal and 12.5% maximal)

Definition at line 108 of file normalizationset.py.

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◆ set_base()

def gdayf.common.normalizationset.NormalizationSet.set_base	(	self,
		datetime = `True`
	)

Method oriented to establish base Normalization [Metadata].

Parameters

self	object pointer

Definition at line 34 of file normalizationset.py.

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◆ set_discretize()

def gdayf.common.normalizationset.NormalizationSet.set_discretize	(	self,
		buckets_number = `10`,
		fixed_size = `True`
	)

Method oriented to establish bucketing actions [Metadata].

Parameters

self	object pointer
buckets_number	Number of buckets to be implemented
fixed_size	True for interval fixed size, False for working on Frequency basis

Definition at line 73 of file normalizationset.py.

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◆ set_drop_missing()

def gdayf.common.normalizationset.NormalizationSet.set_drop_missing ( self )

Method oriented to establish drop_missing Normalization [Metadata].

Parameters

self	object pointer

Definition at line 63 of file normalizationset.py.

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◆ set_fixed_missing_values()

def gdayf.common.normalizationset.NormalizationSet.set_fixed_missing_values	(	self,
		value = `0.0`
	)

Method oriented to establish fixed value imputation data actions into missing values [Metadata].

Parameters

self	object pointer
value	value to be applied into source Dataframe missing values

Definition at line 117 of file normalizationset.py.

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◆ set_ignore_column()

def gdayf.common.normalizationset.NormalizationSet.set_ignore_column ( self )

Method oriented to establish ignore_column Normalization [Metadata].

Parameters

self	object pointer

Definition at line 43 of file normalizationset.py.

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◆ set_mean_missing_values()

def gdayf.common.normalizationset.NormalizationSet.set_mean_missing_values	(	self,
		objective_column,
		full = `False`
	)

Method oriented to establish variable value imputation data actions into missing values based on objective column [Metadata].

Parameters

self	object pointer
objective_column	Objective column string type identification
full	True establishes all value as mean ignoring objective_column. False establishes mean of coincident values on objective column

Definition at line 128 of file normalizationset.py.

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◆ set_offset()

def gdayf.common.normalizationset.NormalizationSet.set_offset	(	self,
		offset = `0`
	)

Method oriented to establish offset (+ or -) data actions [Metadata].

Parameters

self	object pointer
offset	offset value to be applied into source Dataframe

Definition at line 98 of file normalizationset.py.

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◆ set_progressive_missing_values()

def gdayf.common.normalizationset.NormalizationSet.set_progressive_missing_values	(	self,
		objective_column
	)

Method oriented to establish variable extrapolated value imputation data actions into missing values based on objective column [Metadata].

Parameters

self	object pointer
objective_column	Objective column string type identification

Definition at line 139 of file normalizationset.py.

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◆ set_stdmean()

def gdayf.common.normalizationset.NormalizationSet.set_stdmean	(	self,
		mean = `0`,
		std = `1`
	)

Method oriented to establish stdmean Normalization [Metadata].

Parameters

self	object pointer
mean	average data value
std	standard deviation data value

Definition at line 53 of file normalizationset.py.

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◆ set_working_range()

def gdayf.common.normalizationset.NormalizationSet.set_working_range	(	self,
		minval = `-1.0`,
		maxval = `1.0`,
		minrange = `-1.0`,
		maxrange = `1.0`
	)

Method oriented to establish re-scaling data actions [Metadata].

Parameters

self	object pointer
minval	Minimal value on source Dataframe
maxval	Maximum value on source Dataframe
minrange	Minimal value on target Dataframe
minval	Maximum value on target Dataframe

Definition at line 86 of file normalizationset.py.

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The documentation for this class was generated from the following file:

D:/OneDrive/DayF/git/gdayf-core/src/gdayf/common/normalizationset.py

Public Member Functions

Detailed Description

Member Function Documentation

◆ reset()

◆ set_aggregation()

◆ set_base()

◆ set_discretize()

◆ set_drop_missing()

◆ set_fixed_missing_values()

◆ set_ignore_column()

◆ set_mean_missing_values()

◆ set_offset()

◆ set_progressive_missing_values()

◆ set_stdmean()

◆ set_working_range()