参考链接：https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.reset_index.html#pandas-dataframe-reset-index
DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='')[source]
Reset the index, or a level of it.
Reset the index of the DataFrame, and use the default one instead. If the DataFrame has a MultiIndex, this method can remove one or more levels.
- Parameters
- levelint, str, tuple, or list, default None
-
Only remove the given levels from the index. Removes all levels by default.
- dropbool, default False
-
Do not try to insert index into dataframe columns. This resets the index to the default integer index.
- inplacebool, default False
-
Modify the DataFrame in place (do not create a new object).
- col_levelint or str, default 0
-
If the columns have multiple levels, determines which level the labels are inserted into. By default it is inserted into the first level.
- col_fillobject, default ‘’
-
If the columns have multiple levels, determines how the other levels are named. If None then the index name is repeated.
- Returns
- DataFrame or None
-
DataFrame with the new index or None if
inplace=True.
简单来看，就是将索引变成columns内容,col_level与col_fill用在列名为多层索引的。
示例代码
In [59]: df
Out[59]:
class max_speed
falcon bird 389.0
parrot bird 24.0
lion mammal 80.5
monkey mammal NaN
In [60]: df.reset_index()
Out[60]:
index class max_speed
0 falcon bird 389.0
1 parrot bird 24.0
2 lion mammal 80.5
3 monkey mammal NaN
In [61]: df.reset_index(drop=True)
Out[61]:
class max_speed
0 bird 389.0
1 bird 24.0
2 mammal 80.5
3 mammal NaN
In [62]:
上面演示了普通的用法，一个是将index编程了列内容，一个是将index删除了，都用了默认的数字index
后面演示多层索引的示例。
默认情况下，reset_index将会还原所有的索引
In [62]: index = pd.MultiIndex.from_tuples([('bird', 'falcon'),
...: ('bird', 'parrot'),
...: ('mammal', 'lion'),
...: ('mammal', 'monkey')],
...: names=['class', 'name'])
...: columns = pd.MultiIndex.from_tuples([('speed', 'max'),
...: ('species', 'type')])
...: df = pd.DataFrame([(389.0, 'fly'),
...: ( 24.0, 'fly'),
...: ( 80.5, 'run'),
...: (np.nan, 'jump')],
...: index=index,
...: columns=columns)
In [63]: df
Out[63]:
speed species
max type
class name
bird falcon 389.0 fly
parrot 24.0 fly
mammal lion 80.5 run
monkey NaN jump
In [64]: df.reset_index()
Out[64]:
class name speed species
max type
0 bird falcon 389.0 fly
1 bird parrot 24.0 fly
2 mammal lion 80.5 run
3 mammal monkey NaN jump
通过第一个参数的level的设置columns，可以指定需要还原的multiindex的名称
In [75]: df
Out[75]:
speed species
max type
class name
bird falcon 389.0 fly
parrot 24.0 fly
mammal lion 80.5 run
monkey NaN jump
In [76]: df.reset_index(level='class')
Out[76]:
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
In [77]: df.reset_index(level='name')
Out[77]:
name speed species
max type
class
bird falcon 389.0 fly
bird parrot 24.0 fly
mammal lion 80.5 run
mammal monkey NaN jump
In [78]: df.reset_index(level='name', col_level=1)
Out[78]:
speed species
name max type
class
bird falcon 389.0 fly
bird parrot 24.0 fly
mammal lion 80.5 run
mammal monkey NaN jump
In [79]: df.reset_index(level='class', col_level=0, col_fill='type')
Out[79]:
class speed species
type max type
name
falcon bird 389.0 fly
parrot bird 24.0 fly
lion mammal 80.5 run
monkey mammal NaN jump
col_fill参数为设置给mutil_index的默认项