lux.utils package

Submodules

lux.utils.date_utils module

lux.utils.date_utils.compute_date_granularity(date_column: pandas.core.series.Series)

Given a temporal column (pandas.core.series.Series), finds out the granularity of dates.

Example

[‘2018-01-01’, ‘2019-01-02’, ‘2018-01-03’] -> “day” [‘2018-01-01’, ‘2019-02-01’, ‘2018-03-01’] -> “month” [‘2018-01-01’, ‘2019-01-01’, ‘2020-01-01’] -> “year”

Parameters:date_column (pandas.core.series.Series) – Column series with datetime type Returns:field – A str specifying the granularity of dates for the inspected temporal column Return type:str

lux.utils.date_utils.date_formatter(time_stamp, ldf)

Given a numpy timestamp and ldf, inspects which date granularity is appropriate and reformats timestamp accordingly

Example

For changing granularity the results differ as so. days: ‘2020-01-01’ -> ‘2020-1-1’ months: ‘2020-01-01’ -> ‘2020-1’ years: ‘2020-01-01’ -> ‘2020’

Parameters:

• time_stamp (np.datetime64) – timestamp object holding the date information
• ldf (lux.core.frame) – LuxDataFrame with a temporal field

Returns:

date_str – A reformatted version of the time_stamp according to granularity

Return type:

str

lux.utils.date_utils.is_datetime_series(series: pandas.core.series.Series) → bool

Check if the Series object is of datetime type

Parameters:series (pd.Series) – Returns:is_date Return type:bool

lux.utils.date_utils.is_datetime_string(string: str) → bool

Check if the string is date-like.

Parameters:string (str) – Returns:is_date Return type:bool

lux.utils.date_utils.is_timedelta64_series(series: pandas.core.series.Series) → bool

Check if the Series object is of timedelta64 type

Parameters:series (pd.Series) – Returns:is_date Return type:bool

lux.utils.date_utils.timedelta64_to_float_seconds(series: pandas.core.series.Series) → pandas.core.series.Series

Convert a timedelta64 Series to a float Series in seconds

Parameters:series (pd.Series) – Returns:series Return type:pd.Series

lux.utils.utils module

lux.utils.utils.check_if_id_like(df, attribute)

lux.utils.utils.check_if_id_like_for_sql(df, attribute)

lux.utils.utils.check_import_lux_widget()

lux.utils.utils.convert_to_list(x)

“a” –> [“a”] [“a”,”b”] –> [“a”,”b”]

lux.utils.utils.get_agg_title(clause)

lux.utils.utils.get_attrs_specs(intent)

lux.utils.utils.get_filter_specs(intent)

lux.utils.utils.is_numeric_nan_column(series)

lux.utils.utils.like_geo(val)

lux.utils.utils.like_nan(val)

lux.utils.utils.matplotlib_setup(w, h)

lux.utils.utils.pandas_to_lux(df)

Module contents