load_air_pollution¶

getml.datasets.load_air_pollution(roles: bool = True, as_pandas: bool = False) → Union[DataFrame, DataFrame][source]¶

Regression dataset on air pollution in Beijing, China

The dataset consits of a single table split into train and test sets arround 2014-01-01.

The orgininal publication is: Liang, X., Zou, T., Guo, B., Li, S., Zhang, H., Zhang, S., Huang, H. and Chen, S. X. (2015). Assessing Beijing’s PM2.5 pollution: severity, weather impact, APEC and winter heating. Proceedings of the Royal Society A, 471, 20150257.

Args:

as_pandas (bool):: Return data as pandas.DataFrame s
roles (bool):: Return data with roles set

Returns:

getml.data.DataFrame:: A DataFrame holding the data described above.

The following DataFrames are returned:

air_pollution

Examples:

>>> air_pollution = getml.datasets.load_air_pollution()
>>> type(air_pollution)
... getml.data.data_frame.DataFrame

For an full analysis of the atherosclerosis dataset including all necessary preprocessing steps please refer to getml-examples.

Note:

Roles can be set ad-hoc by supplying the respective flag. If roles is False, all columns in the returned DataFrames s have roles unused_string or unused_float. This dataset contains no units. Before using them in an analysis, a data model needs to be constructed using Placeholder s.