In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

__array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0)

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

__array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0)

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

__array_wrap__ must accept context and return_scalar arguments (positionally) in the future. (Deprecated NumPy 2.0)

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

Unexpected input(s) 'file', valid inputs are ['base_sha', 'binary', 'codecov_yml_path', 'commit_parent', 'directory', 'disable_file_fixes', 'disable_search', 'disable_safe_directory', 'disable_telem', 'dry_run', 'env_vars', 'exclude', 'fail_ci_if_error', 'files', 'flags', 'force', 'git_service', 'gcov_args', 'gcov_executable', 'gcov_ignore', 'gcov_include', 'handle_no_reports_found', 'job_code', 'name', 'network_filter', 'network_prefix', 'os', 'override_branch', 'override_build', 'override_build_url', 'override_commit', 'override_pr', 'plugins', 'recurse_submodules', 'report_code', 'report_type', 'root_dir', 'run_command', 'skip_validation', 'slug', 'swift_project', 'token', 'url', 'use_legacy_upload_endpoint', 'use_oidc', 'use_pypi', 'verbose', 'version', 'working-directory']

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning