DataSet.to_pandas

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DataSet.to_pandas#

DataSet.to_pandas(association: PointLiteral | CellLiteral = 'point') → pandas.DataFrame[source]#

Return this dataset’s point or cell arrays as a pandas.DataFrame.

Thin wrapper around DataSetAttributes.to_pandas(). See that method for column-expansion rules and dtype handling.

Requires pandas.

Parameters:
associationstr | pyvista.core.utilities.arrays.FieldAssociation, default: ‘point’

Which attribute set to convert. Accepts 'point' or FieldAssociation.POINT, which maps to point_data (n_points rows); or 'cell' or FieldAssociation.CELL, which maps to cell_data (n_cells rows). Field data is not supported because its arrays may have differing lengths.

Returns:
pandas.DataFrame

DataFrame with one column per (expanded) array.

See also

Export Mesh Data to a DataFrame

Examples

>>> import pyvista as pv
>>> mesh = pv.Cube()
>>> mesh.clear_data()
>>> mesh.point_data['scalars'] = range(mesh.n_points)
>>> df = mesh.to_pandas()
>>> list(df.columns)
['scalars']
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