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hub / github.com/pydata/xarray / to_dataframe

Method to_dataframe

xarray/core/dataset.py:7300–7329  ·  view source on GitHub ↗

Convert this dataset into a pandas.DataFrame. Non-index variables in this dataset form the columns of the DataFrame. The DataFrame is indexed by the Cartesian product of this dataset's indices. Parameters ---------- dim_order: Sequence of Hashable or

(self, dim_order: Sequence[Hashable] | None = None)

Source from the content-addressed store, hash-verified

7298 return broadcasted_df[columns_in_order]
7299
7300 def to_dataframe(self, dim_order: Sequence[Hashable] | None = None) -> pd.DataFrame:
7301 """Convert this dataset into a pandas.DataFrame.
7302
7303 Non-index variables in this dataset form the columns of the
7304 DataFrame. The DataFrame is indexed by the Cartesian product of
7305 this dataset's indices.
7306
7307 Parameters
7308 ----------
7309 dim_order: Sequence of Hashable or None, optional
7310 Hierarchical dimension order for the resulting dataframe. All
7311 arrays are transposed to this order and then written out as flat
7312 vectors in contiguous order, so the last dimension in this list
7313 will be contiguous in the resulting DataFrame. This has a major
7314 influence on which operations are efficient on the resulting
7315 dataframe.
7316
7317 If provided, must include all dimensions of this dataset. By
7318 default, dimensions are in the same order as in `Dataset.sizes`.
7319
7320 Returns
7321 -------
7322 result : DataFrame
7323 Dataset as a pandas DataFrame.
7324
7325 """
7326
7327 ordered_dims = self._normalize_dim_order(dim_order=dim_order)
7328
7329 return self._to_dataframe(ordered_dims=ordered_dims)
7330
7331 def _set_sparse_data_from_dataframe(
7332 self, idx: pd.Index, arrays: list[tuple[Hashable, np.ndarray]], dims: tuple

Calls 2

_normalize_dim_orderMethod · 0.95
_to_dataframeMethod · 0.95