dataprofiler.profilers.datetime_column_profile module¶
Contains class for profiling datetime column.
- class dataprofiler.profilers.datetime_column_profile.DateTimeColumn(name: str | None, options: DateTimeOptions = None)¶
Bases:
BaseColumnPrimitiveTypeProfiler[DateTimeColumn]Datetime column profile subclass of BaseColumnProfiler.
Represents a column int the dataset which is a datetime column.
Initialize it and the column base properties.
- Parameters:
name (String) – Name of the data
options (DateTimeOptions) – Options for the datetime column
- type = 'datetime'¶
- report(remove_disabled_flag: bool = False) dict¶
Return report.
Private abstract method.
- Parameters:
remove_disabled_flag (boolean) – flag to determine if disabled options should be excluded in the report.
- classmethod load_from_dict(data, config: dict | None = None)¶
Parse attribute from json dictionary into self.
- Parameters:
data (dict[string, Any]) – dictionary with attributes and values.
config (Dict | None) – config for loading column profiler params from dictionary
- Returns:
Profiler with attributes populated.
- Return type:
- property profile: dict¶
Return the profile of the column.
- property data_type_ratio: float | None¶
Calculate the ratio of samples which match this data type.
- Returns:
ratio of data type
- Return type:
float
- diff(other_profile: DateTimeColumn, options: dict | None = None) dict¶
Generate differences between max, min, and formats of two DateTime cols.
- Returns:
Dict containing the differences between max, min, and format in their
appropriate output formats :rtype: dict
- update(df_series: Series) DateTimeColumn¶
Update the column profile.
- Parameters:
df_series (pandas.core.series.Series) – df series
- Returns:
None
- col_type = None¶
- match_count: int¶
- sample_size: int¶
- name: str | None¶
- metadata: dict¶
- times: dict¶
- thread_safe: bool¶