fetch_nox

skfda.datasets.fetch_nox(*, return_X_y: typing_extensions.Literal[False] = False, as_frame: bool = False) → Bunch

skfda.datasets.fetch_nox(*, return_X_y: typing_extensions.Literal[True], as_frame: typing_extensions.Literal[False] = False) → Tuple[FDataGrid, ndarray[Any, dtype[int64]]]

skfda.datasets.fetch_nox(*, return_X_y: typing_extensions.Literal[True], as_frame: typing_extensions.Literal[True]) → Tuple[DataFrame, DataFrame]

Load the NOx dataset.

The data is obtained from the R package ‘fda.usc’.

NOx levels measured every hour by a control station in Poblenou in Barcelona (Spain) [1].

References

[1]

Manuel Febrero, Pedro Galeano, and Wenceslao González-Manteiga. Outlier detection in functional data by depth measures, with application to identify abnormal NOx levels. Environmetrics, 19(4):331–345, June 2008. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/env.878 (visited on 2018-12-10), doi:10.1002/env.878.

Parameters:

• return_X_y – Return only the data and target as a tuple.

• as_frame – Return the data in a Pandas Dataframe or Series.