reference/generated/tensordict.TensorDictBase.to_pandas

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TensorDictBase.to_pandas

TensorDictBase.to_pandas(*, separator: str | None = None)

Converts this TensorDict to a pandas DataFrame.

Each leaf key becomes a column. Tensor values are converted to numpy arrays, NonTensorData values are converted to Python lists.

Keyword Arguments:

separator (str, optional) – If provided, nested keys are joined with this separator to produce flat column names. For example, td["obs", "x"] becomes column "obs.x" with separator=".". Required when the TensorDict contains nested sub-TensorDicts. Defaults to None.

Returns:

A pandas DataFrame.

Examples

>>> import torch
>>> from tensordict import TensorDict
>>> td = TensorDict({"a": torch.arange(3), "b": torch.zeros(3)}, [3])
>>> df = td.to_pandas()
>>> print(df)
   a    b
0  0  0.0
1  1  0.0
2  2  0.0

Every tensordict class and every tensorclass has this method. For the other methods, see Methods by task.