Numerical Column Stats

coding=utf-8 Build model for a dataset by identifying type of column along with its respective parameters.

class dataprofiler.profilers.numerical_column_stats.abstractstaticmethod(function)

Bases: staticmethod

class dataprofiler.profilers.numerical_column_stats.NumericStatsMixin(options=None)

Bases: object

Abstract numerical column profile subclass of BaseColumnProfiler. Represents a column in the dataset which is a text column. Has Subclasses itself.

Initialization of column base properties and itself.

Parameters

options (NumericalOptions) – Options for the numerical stats.

type = None

diff(other_profile, options=None)

Finds the differences for several numerical stats.

Parameters

other_profile (NumericStatsMixin Profile) – profile to find the difference with

Returns

the numerical stats differences

Return type

dict

property mean

property variance

property stddev

property skewness

property kurtosis

abstract update(df_series)

Abstract Method for updating the numerical profile properties with an uncleaned dataset.

Parameters

df_series (pandas.core.series.Series) – df series with nulls removed

Returns

None

static is_float(x)

For “0.80” this function returns True For “1.00” this function returns True For “1” this function returns True

Parameters

x (str) – string to test

Returns

if is float or not

Return type

bool

static is_int(x)

For “0.80” This function returns False For “1.00” This function returns True For “1” this function returns True

Parameters

x (str) – string to test

Returns

if is integer or not

Return type

bool

static np_type_to_type(val)

Converts numpy variables to base python type variables

Parameters

val (numpy type or base type) – value to check & change

Return val

base python type

Rtype val

int or float