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.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
- 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¶