pandas --index ,reindex, set_index, reset_index , reindex_like函数 之 reset_index
reset_index(
level: Union[Hashable, Sequence[Hashable], NoneType] = None,
drop: bool = False,
inplace: bool = False,
col_level: Hashable = 0,
col_fill: Union[Hashable, NoneType] = '',
) -> Union[ForwardRef('DataFrame'), NoneType]
Docstring:
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
----------
level : int, str, tuple, or list, default None
Only remove the given levels from the index. Removes all levels by
default.
drop : bool, default False
Do not try to insert index into dataframe columns. This resets
the index to the default integer index.
inplace : bool, default False
Modify the DataFrame in place (do not create a new object).
col_level : int 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_fill : object, 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``.
reset_index()
- 函数原型:DataFrame.reset_index(level=None, drop=False, inplace=False, col_level=0, col_fill='')
- 参数解释:
level:int、str、tuple或list,默认无,仅从索引中删除给定级别。默认情况下移除所有级别。控制了具体要还原的那个等级的索引
drop:drop为False则索引列会被还原为普通列,否则会丢失
inplace:默认为false,适当修改DataFrame(不要创建新对象)
col_level:int或str,默认值为0,如果列有多个级别,则确定将标签插入到哪个级别。默认情况下,它将插入到第一级。
col_fill:对象,默认‘’,如果列有多个级别,则确定其他级别的命名方式。如果没有,则重复索引名 - 注:reset_index还原分为两种类型,第一种是对原DataFrame进行reset,第二种是对使用过set_index()函数的DataFrame进行reset