smif.data_layer.data_array module¶
DataArray provides a thin wrapper around multidimensional arrays and metadata
Summary¶
Data:
DataArray |
DataArray provides access to input/parameter/results data, with conversions to common python data libraries (for example: numpy, pandas, xarray). |
INSTALL_WARNING |
str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str |
find_duplicate_indices |
Find duplicate indices in a DataFrame |
show_null |
Shows missing data |
Reference¶
-
class
smif.data_layer.data_array.
DataArray
(spec: smif.metadata.spec.Spec, data: <MagicMock id='140320896909040'>)[source]¶ Bases:
object
DataArray provides access to input/parameter/results data, with conversions to common python data libraries (for example: numpy, pandas, xarray).
-
spec
¶ Type: smif.metadata.spec.Spec
-
data
¶ Type: numpy.ndarray
-
name
¶ The name of the data that this spec describes.
-
description
¶ A human-friendly description
-
dims
¶ Names for each dimension
-
coords
¶ Coordinate labels for each dimension.
-
unit
¶ The unit for all data points.
-
shape
¶ The shape of the data array
-
as_ndarray
() → <MagicMock id='140320895937952'>[source]¶ Access as a
numpy.ndarray
-
as_df
() → <MagicMock id='140320954868176'>[source]¶ Access DataArray as a
pandas.DataFrame
-
classmethod
from_df
(spec, dataframe)[source]¶ Create a DataArray from a
pandas.DataFrame
-
as_xarray
()[source]¶ Access DataArray as a
xarray.DataArray
-
classmethod
from_xarray
(spec, xr_data_array)[source]¶ Create a DataArray from a
xarray.DataArray
-
-
smif.data_layer.data_array.
show_null
(dataframe) → <MagicMock id='140320954919008'>[source]¶ Shows missing data
Returns: Return type: pandas.DataFrame