API

Contents

API#

Top-level API#

`Not`(value)	Inverted selector value.
`ProcessingStepDescription`(*, time, function, ...)	Structured description of a processing step done on a timeseries.
`TimeseriesProcessingDescription`(steps)	Structured description of all processing steps done on a timeseries.
`accessors`	xarray extension accessors providing an API under the 'pr' namespace.
`open_dataset`(filename_or_obj[, group, ...])	Open and decode a dataset from a file or file-like object.
`ureg`	Unit registry class.

Submodules#

primap2.pm2io#

Data reading module of the PRIMAP2 climate policy analysis package.

`pm2io.convert_long_dataframe_if`(data_long, ...)	Convert a DataFrame in long (tidy) format into the PRIMAP2 interchange format.
`pm2io.convert_wide_dataframe_if`(data_wide, ...)	Convert a DataFrame in wide format into the PRIMAP2 interchange format.
`pm2io.from_interchange_format`(data[, attrs, ...])	Convert dataset from the interchange format to the standard PRIMAP2 format.
`pm2io.nir_add_unit_information`(df_nir, *, ...)	Add unit information to a National Inventory Report (NIR) style DataFrame.
`pm2io.nir_convert_df_to_long`(df_nir, year[, ...])	Convert an entity-wide NIR table for a single year to a long format DataFrame.
`pm2io.read_interchange_format`(filepath)	Read a dataset in the interchange format from disk into memory.
`pm2io.read_long_csv_file_if`(...[, ...])	Read a CSV file in long (tidy) format into the PRIMAP2 interchange format.
`pm2io.read_wide_csv_file_if`(...[, ...])	Read a CSV file in wide format into the PRIMAP2 interchange format.
`pm2io.write_interchange_format`(filepath, data)	Write dataset in interchange format to disk.

primap2.csg#

Composite Source Generator

Generate a composite harmonized dataset from multiple sources according to defined source priorities and matching algorithms.

`csg.GlobalLSStrategy`([allow_shift, ...])	Fill missing data by global least square matching.
`csg.PriorityDefinition`(*, ...[, ...])	Defines source priorities for composing a full dataset or a single timeseries.
`csg.StrategyDefinition`(strategies)	Defines filling strategies for a single timeseries.
`csg.StrategyUnableToProcess`(reason)	The filling strategy is unable to process the given timeseries, possibly due to missing data.
`csg.SubstitutionStrategy`()	Fill missing data in the result dataset by copying.
`csg.compose`(*, input_data, ...[, progress_bar])	Compose a harmonized dataset from multiple input datasets.

DataArray#

Attributes#

`DataArray.pr.dim_alias_translations`	Translate a shortened dimension alias to a full dimension name.
`DataArray.pr.gwp_context`	The pint conversion context for this DataArray, directly usable for conversions.
`DataArray.pr.loc`	Location-based indexing like xr.DataArray.loc with added features.

Methods#

`DataArray.pr.__getitem__`(item)	Like da[], but translates short aliases like "area" into the long names including the corresponding category-set.
`DataArray.pr.add_aggregates_coordinates`(agg_info)	Manually aggregate data for coordinates
`DataArray.pr.any`([dim, keep_attrs])	Reduce this DataArray's data by applying `any` along some dimension(s).
`DataArray.pr.combine_first`(da_combine)	Combine data from multiple arrays.
`DataArray.pr.convert_to_gwp`(gwp_context, units)	Convert to a global warming potential
`DataArray.pr.convert_to_gwp_like`(like)	Convert to a global warming potential in the units of a reference array.
`DataArray.pr.convert_to_mass`([gwp_context, ...])	Convert a global warming potential of a greenhouse gas to a mass.
`DataArray.pr.count`([dim, reduce_to_dim, ...])	Reduce this array by counting along some dimension(s).
`DataArray.pr.coverage`(*dims)	Summarize how many data points exist for a dimension combination.
`DataArray.pr.dequantify`()	Removes units from the DataArray and its coordinates.
`DataArray.pr.downscale_timeseries`(*, dim, ...)	Downscale timeseries along a dimension using a basket defined on a broader timeseries.
`DataArray.pr.fill_all_na`(dim[, value])	Fill NA values only where all values along the specified dimension(s) are NA.
`DataArray.pr.fillna`(da_fill)	Fill missing information from other array.
`DataArray.pr.merge`(da_merge[, tolerance, ...])	Merge with da_merge with a tolerance for discrepancies in values found in both.
`DataArray.pr.quantify`(**kwargs)	Attaches units to the DataArray.
`DataArray.pr.set`(dim, key, value, *[, ...])	Set values, optionally expanding the given dimension as necessary.
`DataArray.pr.sum`([dim, reduce_to_dim, ...])	Reduce this DataArray's data by applying `sum` along some dimension(s).
`DataArray.pr.to_df`([name])	Convert this array into an unstacked (i.e. non-tidy) pandas.DataFrame.

Dataset#

Attributes#

`Dataset.pr.comment`	Longer form description
`Dataset.pr.contact`	Who can answer questions about the data
`Dataset.pr.dim_alias_translations`	Translate a shortened dimension alias to a full dimension name.
`Dataset.pr.entity_terminology`	The terminology of the entity attributes in this dataset's data variables
`Dataset.pr.institution`	Where the data originates
`Dataset.pr.loc`	Location-based indexing like xr.DataArray.loc with added features.
`Dataset.pr.publication_date`	The original date of publication of the dataset, if published.
`Dataset.pr.references`	Citable reference(s) describing the data
`Dataset.pr.rights`	License or other usage restrictions of the data
`Dataset.pr.title`	A succinct description

Methods#

`Dataset.pr.__getitem__`(item)	Like ds[], but translates short aliases like "area" into the long names including the corresponding category-set.
`Dataset.pr.add_aggregates_coordinates`(agg_info)	Manually aggregate data for coordinates
`Dataset.pr.add_aggregates_variables`(gas_baskets)	Creates or fills gas baskets
`Dataset.pr.any`([dim, keep_attrs])	Reduce this Dataset's data by applying `any` along some dimension(s).
`Dataset.pr.combine_first`(ds_combine)	Combine with data from other dataset or array.
`Dataset.pr.count`([dim, reduce_to_dim, ...])	Reduce this Dataset by counting along some dimension(s).
`Dataset.pr.coverage`(*dims)	Summarize how many data points exist for a dimension combination.
`Dataset.pr.dequantify`()	Removes units from the Dataset and its coordinates.
`Dataset.pr.downscale_gas_timeseries`(*, ...)	Downscale a gas basket defined on a broader timeseries to its contents known on fewer time points.
`Dataset.pr.downscale_timeseries`(*, dim, ...)	Downscale timeseries along a dimension using a basket defined on a broader timeseries.
`Dataset.pr.ensure_valid`()	Ensure this is a valid primap2 data set.
`Dataset.pr.expand_dims`(dim, coord_value[, ...])	Add a dimension and coordinate to dataset.
`Dataset.pr.fill_all_na`(dim[, value])	Fill NA values only where all values along the specified dimension(s) are NA.
`Dataset.pr.fill_na_gas_basket_from_contents`(*, ...)	Fill NA values in a gas basket using the sum of its contents.
`Dataset.pr.fillna`(ds_fill)	Fill missing information from other dataset.
`Dataset.pr.gas_basket_contents_sum`(*, ...[, ...])	The sum of gas basket contents converted using the global warming potential of the gas basket.
`Dataset.pr.has_processing_info`()	True if the dataset has processing information for at least one entity.
`Dataset.pr.merge`(ds_merge[, tolerance, ...])	Merge two Datasets with a tolerance for discrepancies in values present in both Datasets.
`Dataset.pr.quantify`([units])	Attaches units to each variable in the Dataset.
`Dataset.pr.remove_processing_info`()	Return dataset with all variables with processing information removed.
`Dataset.pr.set`(dim, key, value, *[, ...])	Set values, optionally expanding the given dimension as necessary.
`Dataset.pr.sum`([dim, reduce_to_dim, skipna, ...])	Reduce this Dataset's data by applying `sum` along some dimension(s).
`Dataset.pr.to_df`([name])	Convert this dataset into a pandas.DataFrame.
`Dataset.pr.to_interchange_format`([time_format])	Convert dataset to the interchange format.
`Dataset.pr.to_netcdf`(path[, mode, group, ...])	Write dataset contents to a netCDF file.