6.10 Starting a Standardisation Process

Within a project object one method (routine) is available to define and start a standardisation process. Assuming that a project object has been created (by copying and modifying the template module project-standardise.py) and input and output data sets, as well as component and a record standardisers have been defined, standardisation of a data set can be done by one simple call to the method standardise as shown in the following example.

# ====================================================================

myproject.standardise(input_dataset = hospital_data,
                     output_dataset = clean_hospital_data,
                   rec_standardiser = hospital_standardiser,
                       first_record = 0,
                     number_records = 100000)

In the given example, 100,000 records in a fictitious hospital data set are standardised and written into an output data set (assuming it has been initialised).

The following arguments need to be defined for the standardisation process.

input_dataset
A reference to a data set which contains the (raw) input data. This data must be initialised in read access mode.
output_dataset
A reference to an output data set, which has been initialised in write, readwrite or append access mode. This output data set can be any data set implementation except a memory based data set (as all standardised records would be lost once the program finishes). See Chapter 13 for more information on data set implementations.
rec_standardiser
A reference to a record standardiser. See Section 6.9 for more details on how to initialise a record standardiser.
first_record
The record number of the first record in the input data set to be processed. If this argument is not given or set to None (default), the first record (i.e. record with number 0) is taken.
number_records
The number of records from the input data set that should be processed. If this argument is not given, all records in the input data set are processed.