@@ -408,8 +408,10 @@ def _get_op_name(op, special):
408408----------
409409other : Series or scalar value
410410fill_value : None or float value, default None (NaN)
411- Fill missing (NaN) values with this value. If both Series are
412- missing, the result will be missing
411+ Fill existing missing (NaN) values, and any new element needed for
412+ successful Series alignment, with this value before computation.
413+ If data in both corresponding Series locations is missing
414+ the result will be missing
413415level : int or name
414416 Broadcast across a level, matching Index values on the
415417 passed MultiIndex level
@@ -418,6 +420,30 @@ def _get_op_name(op, special):
418420-------
419421result : Series
420422
423+ Examples
424+ --------
425+ >>> a = pd.Series([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'])
426+ >>> a
427+ a 1.0
428+ b 1.0
429+ c 1.0
430+ d NaN
431+ dtype: float64
432+ >>> b = pd.Series([1, np.nan, 1, np.nan], index=['a', 'b', 'd', 'e'])
433+ >>> b
434+ a 1.0
435+ b NaN
436+ d 1.0
437+ e NaN
438+ dtype: float64
439+ >>> a.add(b, fill_value=0)
440+ a 2.0
441+ b 1.0
442+ c 1.0
443+ d 1.0
444+ e NaN
445+ dtype: float64
446+
421447See also
422448--------
423449Series.{reverse}
@@ -433,8 +459,10 @@ def _get_op_name(op, special):
433459axis : {0, 1, 'index', 'columns'}
434460 For Series input, axis to match Series index on
435461fill_value : None or float value, default None
436- Fill missing (NaN) values with this value. If both DataFrame locations are
437- missing, the result will be missing
462+ Fill existing missing (NaN) values, and any new element needed for
463+ successful DataFrame alignment, with this value before computation.
464+ If data in both corresponding DataFrame locations is missing
465+ the result will be missing
438466level : int or name
439467 Broadcast across a level, matching Index values on the
440468 passed MultiIndex level
@@ -446,6 +474,33 @@ def _get_op_name(op, special):
446474Returns
447475-------
448476result : DataFrame
477+
478+ Examples
479+ --------
480+ >>> a = pd.DataFrame([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'],
481+ columns=['one'])
482+ >>> a
483+ one
484+ a 1.0
485+ b 1.0
486+ c 1.0
487+ d NaN
488+ >>> b = pd.DataFrame(dict(one=[1, np.nan, 1, np.nan],
489+ two=[np.nan, 2, np.nan, 2]),
490+ index=['a', 'b', 'd', 'e'])
491+ >>> b
492+ one two
493+ a 1.0 NaN
494+ b NaN 2.0
495+ d 1.0 NaN
496+ e NaN 2.0
497+ >>> a.add(b, fill_value=0)
498+ one two
499+ a 2.0 NaN
500+ b 1.0 2.0
501+ c 1.0 NaN
502+ d 1.0 NaN
503+ e NaN 2.0
449504"""
450505
451506_flex_doc_FRAME = """
@@ -460,8 +515,10 @@ def _get_op_name(op, special):
460515axis : {{0, 1, 'index', 'columns'}}
461516 For Series input, axis to match Series index on
462517fill_value : None or float value, default None
463- Fill missing (NaN) values with this value. If both DataFrame
464- locations are missing, the result will be missing
518+ Fill existing missing (NaN) values, and any new element needed for
519+ successful DataFrame alignment, with this value before computation.
520+ If data in both corresponding DataFrame locations is missing
521+ the result will be missing
465522level : int or name
466523 Broadcast across a level, matching Index values on the
467524 passed MultiIndex level
@@ -474,6 +531,33 @@ def _get_op_name(op, special):
474531-------
475532result : DataFrame
476533
534+ Examples
535+ --------
536+ >>> a = pd.DataFrame([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'],
537+ columns=['one'])
538+ >>> a
539+ one
540+ a 1.0
541+ b 1.0
542+ c 1.0
543+ d NaN
544+ >>> b = pd.DataFrame(dict(one=[1, np.nan, 1, np.nan],
545+ two=[np.nan, 2, np.nan, 2]),
546+ index=['a', 'b', 'd', 'e'])
547+ >>> b
548+ one two
549+ a 1.0 NaN
550+ b NaN 2.0
551+ d 1.0 NaN
552+ e NaN 2.0
553+ >>> a.add(b, fill_value=0)
554+ one two
555+ a 2.0 NaN
556+ b 1.0 2.0
557+ c 1.0 NaN
558+ d 1.0 NaN
559+ e NaN 2.0
560+
477561See also
478562--------
479563DataFrame.{reverse}
@@ -545,7 +629,6 @@ def _make_flex_doc(op_name, typ):
545629 base_doc = _flex_doc_PANEL
546630 else :
547631 raise AssertionError ('Invalid typ argument.' )
548-
549632 doc = base_doc .format (desc = op_desc ['desc' ], op_name = op_name ,
550633 equiv = equiv , reverse = op_desc ['reverse' ])
551634 return doc
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