Float Column Profile¶
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class
dataprofiler.profilers.float_column_profile.FloatColumn(name, options=None)¶ Bases:
dataprofiler.profilers.numerical_column_stats.NumericStatsMixin,dataprofiler.profilers.base_column_profilers.BaseColumnPrimitiveTypeProfilerFloat 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
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type= 'float'¶
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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
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property
profile¶ Property for profile. Returns the profile of the column. :return:
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property
precision¶ Property reporting statistics on the significant figures of each element in the data. :return: Precision statistics :rtype: dict
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property
data_type_ratio¶ Calculates the ratio of samples which match this data type. :return: ratio of data type :rtype: float
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col_type= None¶
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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
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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
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property
kurtosis¶
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property
mean¶
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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
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property
skewness¶
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property
stddev¶
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update(df_series)¶ Updates the column profile. :param df_series: df series :type df_series: pandas.core.series.Series :return: None
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property
variance¶
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