Float Column Profile

class dataprofiler.profilers.float_column_profile.FloatColumn(name, options=None)

Bases: dataprofiler.profilers.numerical_column_stats.NumericStatsMixin, dataprofiler.profilers.base_column_profilers.BaseColumnPrimitiveTypeProfiler

Float column profile mixin with of numerical stats. Represents a column in the dataset which is a float column.

Initialization of column base properties and itself. :param name: Name of the data :type name: String :param options: Options for the float column :type options: FloatOptions

type = 'float'
diff(other_profile, options=None)

Finds the differences for FloatColumns.

Parameters

other_profile (FloatColumn) – profile to find the difference with

Returns

the FloatColumn differences

Return type

dict

property profile

Property for profile. Returns the profile of the column. :return:

property precision

Property reporting statistics on the significant figures of each element in the data. :return: Precision statistics :rtype: dict

property data_type_ratio

Calculates the ratio of samples which match this data type. :return: ratio of data type :rtype: float

col_type = 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

property kurtosis
property mean
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

property skewness
property stddev
update(df_series)

Updates the column profile. :param df_series: df series :type df_series: pandas.core.series.Series :return: None

property variance