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DOC: Add more examples for reset_index #17055

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Jul 23, 2017
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DOC: Add more examples for reset_index #17055

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64 changes: 37 additions & 27 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3060,57 +3060,67 @@ class max_speed
... ('mammal', 'monkey')],
... names=['class', 'name'])
>>> columns = pd.MultiIndex.from_tuples([('speed', 'max'),
... ('speed', 'type')])
... ('species', 'type')])
>>> df = pd.DataFrame([(389.0, 'fly'),
... ( 24.0, 'fly'),
... ( 80.5, 'run'),
... (np.nan, 'jump')],
... index=index,
... columns=columns)
>>> df
speed
max type
speed species
max type
class name
bird falcon 389.0 fly
parrot 24.0 fly
mammal lion 80.5 run
monkey NaN jump
bird falcon 389.0 fly
parrot 24.0 fly
mammal lion 80.5 run
monkey NaN jump

If the index has multiple levels, we can reset a subset of them:

>>> df.reset_index(level='class')
class speed
max type
class speed species
max type
name
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump

If we are not dropping the index, by default, it is placed in the top
level. We can place it in another level:

>>> df.reset_index(level='class', col_level=1)
speed
class max type
speed species
class max type
name
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump

When the index is inserted under another level, we can specify under
which one with the parameter `col_fill`. If we specify a nonexistent
level, it is created:
which one with the parameter `col_fill`:

>>> df.reset_index(level='class', col_level=1, col_fill='species')
species speed
class max type
species speed species
class max type
name
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump

If we specify a nonexistent level for `col_fill`, it is created:

>>> df.reset_index(level='class', col_level=1, col_fill='genus')
genus speed species
class max type
name
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if inplace:
Expand Down