DOC: Fixed examples in pandas/core/groupby/

[ShaharNaveh]

• closes #xxxx
• tests added / passed
• passes black pandas
• passes git diff upstream/master -u -- "*.py" | flake8 --diff
• whatsnew entry

[WillAyd]

Does this still render as code when you build the docs?

[ShaharNaveh]

Good catch!

---

Fixed in 4f1b138

[WillAyd]

Is keeping this as it was not an option? I don’t think we add code-blocks to docstring normally since they are oriented more towards generated HTML / PDF output and aren’t super useful in say a shell

[ShaharNaveh]

The only solution that comes to my mind is to add # doctest: +SKIP to this.

[WillAyd]

@jreback do you know how we typically handle these? I don't think we use code-block in docstrings do we?

[ShaharNaveh]

@WillAyd We actually do: (although I'm not sure if this is wanted)

pandas/pandas/core/accessor.py

Lines 223 to 266 in cabc31a

	.. code-block:: python
	def __init__(self, pandas_object): # noqa: E999
	...
	For consistency with pandas methods, you should raise an ``AttributeError``
	if the data passed to your accessor has an incorrect dtype.
	>>> pd.Series(['a', 'b']).dt
	Traceback (most recent call last):
	...
	AttributeError: Can only use .dt accessor with datetimelike values
	Examples
	--------
	In your library code::
	import pandas as pd
	@pd.api.extensions.register_dataframe_accessor("geo")
	class GeoAccessor:
	def __init__(self, pandas_obj):
	self._obj = pandas_obj
	@property
	def center(self):
	# return the geographic center point of this DataFrame
	lat = self._obj.latitude
	lon = self._obj.longitude
	return (float(lon.mean()), float(lat.mean()))
	def plot(self):
	# plot this array's data on a map, e.g., using Cartopy
	pass
	Back in an interactive IPython session:
	.. code-block:: ipython
	In [1]: ds = pd.DataFrame({{"longitude": np.linspace(0, 10),
	...: "latitude": np.linspace(0, 20)}})
	In [2]: ds.geo.center
	Out[2]: (5.0, 10.0)
	In [3]: ds.geo.plot() # plots data on a map

[datapythonista]

May be using triple backticks? Otherwise, a skip seems reasonable. Or may be @jorisvandenbossche has a better idea.

[datapythonista]

lgtm, thanks @MomIsBestFriend

[WillAyd]

Thanks @MomIsBestFriend