mqr.process.

Summary#

class mqr.process.Summary(data, specs=None, conf=0.95, ddof=1)#

Measurements and summary statistics for a set of samples from a process.

Attributes:

datapd.DataFrame: Measurements with KPIs in each column, and possibly other columns like run lables, operator IDs, etc.
samplesdict[str, mqr.process.Sample]: Automatically constructed. Dict of mqr.process.Sample for each sample in data.
capabilitiesdict[str, Capability]: Automatically constructed when initialised with Specification`s. Dict of `mqr.process.Capability for each sample in data.

Examples

Construct this object using a dataframe of measurements, optionally providing a list of columns to include:

>>> data = pd.read_csv(mqr.sample_data('study-random-5x5.csv'))
>>> mqr.process.Study(data)

That input is shown in notebooks as an HTML table: