gooddata_pandas.series.SeriesFactory

class gooddata_pandas.series.SeriesFactory(sdk: GoodDataSdk, workspace_id: str)

Bases: object

__init__(sdk: GoodDataSdk, workspace_id: str) → None

Methods

__init__(sdk, workspace_id)
indexed(index_by, data_by[, filter_by])	Creates pandas Series from data points calculated from a single data_by that will be computed on granularity of the index labels.
not_indexed(data_by[, granularity, filter_by])	Creates pandas Series from data points calculated from a single data_by that will be computed on granularity of the specified labels.

indexed(index_by: IndexDef, data_by: Union[SimpleMetric, str, ObjId, Attribute], filter_by: Optional[Union[Filter, list[Filter]]] = None) → pandas.Series

Creates pandas Series from data points calculated from a single data_by that will be computed on granularity of the index labels. The elements of the index labels will be used to construct simple or hierarchical index.

Parameters:

• index_by –

  label to index by; specify either:

  • string with id: some_label_id,

  • object identifier: ObjId(id='some_label_id', type='label'),

  • string representation of object identifier: label/some_label_id

  • or an Attribute object used in the compute model: Attribute(local_id=..., label='some_label_id')

  • dict containing mapping of index name to label to use for indexing - specified in one of the ways list above

• data_by –

  label, fact or metric to that will provide data (metric values or label elements); specify either:

  • object identifier: ObjId(id='some_id', type='<type>') - where type is either label, fact or metric

  • string representation of object identifier: <type>/some_id - where type is either label, fact or metric

  • Attribute object used in the compute model: Attribute(local_id=..., label='some_label_id')

  • SimpleMetric object used in the compute model: SimpleMetric(local_id=..., item=..., aggregation=...)

• filter_by –

  optionally specify filter to apply during computation on the server, reference to filtering column can be one of:

  • string reference to index key

  • object identifier in string form

  • object identifier: ObjId(id='some_label_id', type='<type>')

  • Attribute or Metric depending on type of filter

Returns:

pandas series instance

not_indexed(data_by: Union[SimpleMetric, str, ObjId, Attribute], granularity: Optional[Union[list[LabelItemDef], IndexDef]] = None, filter_by: Optional[Union[Filter, list[Filter]]] = None) → pandas.Series

Creates pandas Series from data points calculated from a single data_by that will be computed on granularity of the specified labels. No index will be constructed.

Note that data_by may also be a label in which case the Series will contain label elements.

Parameters:

• data_by –

  label, fact or metric to get data from; specify either:

  • object identifier: ObjId(id='some_id', type='<type>') - where type is either label, fact or metric

  • string representation of object identifier: <type>/some_id - where type is either label, fact or metric

  • Attribute object used in the compute model: Attribute(local_id=..., label='some_label_id')

  • SimpleMetric object used in the compute model: SimpleMetric(local_id=..., item=..., aggregation=...)

• granularity –

  optionally specify label to slice the metric by; specify either:

  • string with id: some_label_id,

  • object identifier: ObjId(id='some_label_id', type='label'),

  • string representation of object identifier: label/some_label_id

  • or an Attribute object used in the compute model: Attribute(local_id=..., label='some_label_id')

  • list containing multiple labels to slice the metric by - specified in one of the ways list above

  • dict containing mapping of index name to label to use for indexing - specified in one of the ways list above; this option is available so that you can easily switch from indexed factory method to this one if needed

• filter_by –

  optionally specify filter to apply during computation on the server, reference to filtering column can be one of:

  • object identifier in string form

  • object identifier: ObjId(id='some_label_id', type='<type>')

  • Attribute or Metric depending on type of filter

Returns:

pandas series instance