DOC: correct example use of nth dropna keyword (#17641)

jorisvandenbossche · jreback · commit e2757a2db0fa · 2017-09-23T10:13:01.000-04:00
dropna=True is deprecated, see #17493
diff --git a/doc/source/groupby.rst b/doc/source/groupby.rst
@@ -1060,7 +1060,7 @@ To select from a DataFrame or Series the nth item, use the nth method. This is a
    g.nth(-1)
    g.nth(1)
 
-If you want to select the nth not-null item, use the ``dropna`` kwarg. For a DataFrame this should be either ``'any'`` or ``'all'`` just like you would pass to dropna, for a Series this just needs to be truthy.
+If you want to select the nth not-null item, use the ``dropna`` kwarg. For a DataFrame this should be either ``'any'`` or ``'all'`` just like you would pass to dropna:
 
 .. ipython:: python
 
@@ -1072,7 +1072,7 @@ If you want to select the nth not-null item, use the ``dropna`` kwarg. For a Dat
    g.nth(-1, dropna='any')  # NaNs denote group exhausted when using dropna
    g.last()
 
-   g.B.nth(0, dropna=True)
+   g.B.nth(0, dropna='all')
 
 As with other methods, passing ``as_index=False``, will achieve a filtration, which returns the grouped row.
 

Original file line number	Original file line	Diff line number	Diff line change
`@@ -1060,7 +1060,7 @@ To select from a DataFrame or Series the nth item, use the nth method. This is a`
`1060`	`g.nth(-1)`	`1060`	`g.nth(-1)`
`1061`	`g.nth(1)`	`1061`	`g.nth(1)`
`1062`		`1062`
`1063`	-If you want to select the nth not-null item, use the ``dropna`` kwarg. For a DataFrame this should be either ``'any'`` or ``'all'`` just like you would pass to dropna, for a Series this just needs to be truthy.	`1063`	+If you want to select the nth not-null item, use the ``dropna`` kwarg. For a DataFrame this should be either ``'any'`` or ``'all'`` just like you would pass to dropna:
`1064`		`1064`
`1065`	`.. ipython:: python`	`1065`	`.. ipython:: python`
`1066`		`1066`
@@ -1072,7 +1072,7 @@ If you want to select the nth not-null item, use the ``dropna`` kwarg. For a Dat
`1072`	`g.nth(-1, dropna='any') # NaNs denote group exhausted when using dropna`	`1072`	`g.nth(-1, dropna='any') # NaNs denote group exhausted when using dropna`
`1073`	`g.last()`	`1073`	`g.last()`
`1074`		`1074`
`1075`	`- g.B.nth(0, dropna=True)`	`1075`	`+ g.B.nth(0, dropna='all')`
`1076`		`1076`
`1077`	As with other methods, passing ``as_index=False``, will achieve a filtration, which returns the grouped row.	`1077`	As with other methods, passing ``as_index=False``, will achieve a filtration, which returns the grouped row.
`1078`		`1078`