time_stream.qc.TimeRangeCheck

class time_stream.qc.TimeRangeCheck(min_value, max_value, closed='both', within=True)

Flag rows where the primary time column of the time series fall within an acceptable range.

This can either be used with min / max values of:

• datetime.timeUseful for scenarios where there are consistent errors at a certain time of day,

  e.g., during an automated sensor calibration time.

• datetime.dateUseful for scenarios where a specific date range is known to be bad,

  e.g., during a time of sensor errors not picked up elsewhere.

• datetime.datetime : As above, but where there you need to add a time to the date range as well.

Note: This is equivalent to using RangeCheck with check_column = ts.time_name. However, adding this as a

convenience method as it may not be obvious that the RangeCheck can be used for this purpose.

Parameters:

• min_value (float | time | date | datetime)

• max_value (float | time | date | datetime)

• closed (str | ClosedInterval)

• within (bool)

__init__(min_value, max_value, closed='both', within=True)

Initialise range check.

Parameters:

• min_value (float | time | date | datetime) – Minimum of the range.

• max_value (float | time | date | datetime) – Maximum of the range.

• closed (str | ClosedInterval) – Define which sides of the interval are closed (inclusive) {‘both’, ‘left’, ‘right’, ‘none’} (default = “both”)

• within (bool) – Whether values get flagged when within or outside the range (default = True (within)).

Return type:

None

Methods

__init__(min_value, max_value[, closed, within])	Initialise range check.
apply(df, time_name, check_column[, ...])	Apply the QC check to the data.
available()	Return a sorted list of available registered keys.
expr(ctx, column)	Return the Polars expression for range checking.
get(spec, **kwargs)	Resolve spec to an instance of Self:
register(register_cls)	A method used as a decorator for subclasses to add to the register by its name attribute.

Attributes

name