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DOC: fix the pandas.DataFrame.add example #20077

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Merged
merged 5 commits into from
Mar 15, 2018
Merged

DOC: fix the pandas.DataFrame.add example #20077

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d58c4fe
fixed 'Wrong parameter order' validation error
robinkiplangat Mar 9, 2018
736972d
added use of ‘…’ to pass doctests
robinkiplangat Mar 9, 2018
2e36068
adjustment to indentation
robinkiplangat Mar 9, 2018
5833bb6
Merge remote-tracking branch 'upstream/master' into 4bic-improved_doc…
jorisvandenbossche Mar 15, 2018
ca3e5f9
fix alignment
jorisvandenbossche Mar 15, 2018
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18 changes: 9 additions & 9 deletions pandas/core/ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -477,16 +477,16 @@ def _get_op_name(op, special):
Examples
--------
>>> a = pd.DataFrame([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'],
columns=['one'])
... columns=['one'])
>>> a
one
a 1.0
b 1.0
c 1.0
d NaN
>>> b = pd.DataFrame(dict(one=[1, np.nan, 1, np.nan],
two=[np.nan, 2, np.nan, 2]),
index=['a', 'b', 'd', 'e'])
... two=[np.nan, 2, np.nan, 2]),
... index=['a', 'b', 'd', 'e'])
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May need one more space here, so that the "i" in "index" is below the "d" in "dict'.

>>> b
one two
a 1.0 NaN
Expand All @@ -513,14 +513,14 @@ def _get_op_name(op, special):
other : Series, DataFrame, or constant
axis : {{0, 1, 'index', 'columns'}}
For Series input, axis to match Series index on
level : int or name
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I think level : int or str, though we're inconsistent here.

@jorisvandenbossche what should our policy be on index positions or labels? In principle, int or str isn't quite right since index labels needn't be strings. It'd be int or object, which isn't that informative. int or label?

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Hmm, yes, this is a dubious one. "name" is technically not a 'type', but "str" would not be correct as you say. So maybe better to keep it that way.

If we keep the 'name' or 'label', wouldn't 'name' be better because it is here a index level name, not a label inside the index ?

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Ah, yes you're right I was mistaken.

And we can declare that "name" means anything that can go in {.index,.columns}{.name,.names}.

Broadcast across a level, matching Index values on the
passed MultiIndex level
fill_value : None or float value, default None
Fill existing missing (NaN) values, and any new element needed for
successful DataFrame alignment, with this value before computation.
If data in both corresponding DataFrame locations is missing
the result will be missing
level : int or name
Broadcast across a level, matching Index values on the
passed MultiIndex level

Notes
-----
Expand All @@ -533,16 +533,16 @@ def _get_op_name(op, special):
Examples
--------
>>> a = pd.DataFrame([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'],
columns=['one'])
... columns=['one'])
>>> a
one
a 1.0
b 1.0
c 1.0
d NaN
>>> b = pd.DataFrame(dict(one=[1, np.nan, 1, np.nan],
two=[np.nan, 2, np.nan, 2]),
index=['a', 'b', 'd', 'e'])
... two=[np.nan, 2, np.nan, 2]),
... index=['a', 'b', 'd', 'e'])
>>> b
one two
a 1.0 NaN
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