metobs_toolkit.Dataset.get_gaps_df

Dataset.get_gaps_df()

List all gaps into an overview dataframe.

Returns:

A DataFrame with stationnames as index, and the start, end and duretion of the gaps as columns.

Return type:

pandas.DataFrame

Examples

>>> import metobs_toolkit
>>>
>>> # Import data into a Dataset
>>> dataset = metobs_toolkit.Dataset()
>>> dataset.update_settings(
...                         input_data_file=metobs_toolkit.demo_datafile,
...                         input_metadata_file=metobs_toolkit.demo_metadatafile,
...                         template_file=metobs_toolkit.demo_template,
...                         )
>>> dataset.import_data_from_file()
>>> dataset.coarsen_time_resolution(freq='1H')
>>>
>>> # Apply quality control on the temperature observations
>>> dataset.apply_quality_control(obstype='temp') #Using the default QC settings
>>>
>>> # Interpret the outliers as missing/gaps
>>> dataset.update_gaps_and_missing_from_outliers(obstype='temp')
>>> dataset
Dataset instance containing:
     *28 stations
     *['temp', 'humidity', 'radiation_temp', 'pressure', 'pressure_at_sea_level', 'precip', 'precip_sum', 'wind_speed', 'wind_gust', 'wind_direction'] observation types
     *10080 observation records
     *235 records labeled as outliers
     *2 gaps
     *1473 missing observations
     *records range: 2022-09-01 00:00:00+00:00 --> 2022-09-15 23:00:00+00:00 (total duration:  14 days 23:00:00)
     *time zone of the records: UTC
     *Coordinates are available for all stations.
>>> dataset.get_gaps_df()
                          start_gap                   end_gap        duration
name
vlinder05 2022-09-06 21:00:00+00:00 2022-09-13 06:00:00+00:00 6 days 09:00:00
vlinder05 2022-09-13 20:00:00+00:00 2022-09-15 23:00:00+00:00 2 days 03:00:00