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EconomicSeries

EconomicSeries#

class sigtech.framework.instruments.economic_series.EconomicSeries

Baseclasses: HistoricalFrameworkObject

A class representing a Economic series

aggregation_type: int
property data_source_all

Data sources of the instrument.

data_type: str
database: str
description: str
property due_time

Required for parent class

Returns:

None

frequency: str
geography: int
group_name: str
schedule_start: Optional[date]
series_name: str
property timezone: str

Returns the timezone

Returns:

the timezone identifier as a string

data_df(data_point: DataPoint = None, multi_index: bool = False, drop_nan_cols: bool = False, pretty_print=True) → DataFrame

Return a DataFrame containing all data available for this object.

Parameters:

  • data_point – Optional data point used to load the object history.

  • multi_index – If set to True, rows are uniquely indexed by a multi index (if applicable). Default is False.

  • drop_nan_cols – If set to True, all-NaN columns are dropped. Default is False.

  • pretty_print – If set to True, formatting is added to columns names and data values. Rates will be represented as percentage number instead of decimal number (e.g. 3.5 instead of 0.035).

Returns:

pandas DataFrame.

get_series(field: str = None, date_index: bool = False, include_internal_id: bool = False) → Union[Series, DataFrame] deprecated

Deprecated method to retrieve time series for objects If the given field does not exist, an empty series will be returned.

Parameters:

  • field – Optional - Which revision of a date’s reading to use. Must be one of the history fields.

  • date_index – Optional - Set index to the ‘date’ column, default behaviour

  • include_internal_id – Optional - Include the internal id in returned timeframe, removed by default

Returns:

pd.Series.

history(field: str = None, date_index: bool = True, adjust_for_delay: bool = False, data_point: Optional[DataPoint] = None, datetime_index: bool = False) → Union[Series, DataFrame]

Method to retrieve time series for objects If the given field does not exist, an empty series will be returned.

Parameters:

  • field – Optional - Which revision of a date’s reading to use. Must be one of

  • date_index – Optional - convert date column to index, default behaviour.

  • adjust_for_delay – Not supported

  • data_point – Not supported

  • datetime_index – Not supported

Returns:

pd.Series.

holidays()

Returns the name of the holiday calendar associated with this Fix

Returns:

The name of the holiday calendar