pandas.DataFrame.reset_index#

DataFrame.reset_index(level=None,*,drop=False,inplace=False,col_level=0,col_fill='',allow_duplicates=<no_default>,names=None)[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 morelevels.

Parameters:

levelint, str, tuple, or list, default None

Only remove the given levels from the index. Removes all levels bydefault.

dropbool, default False

Do not try to insert index into dataframe columns. This resetsthe index to the default integer index.

inplacebool, default False

Whether to modify the DataFrame rather than creating a new one.

col_levelint or str, default 0

If the columns have multiple levels, determines which level thelabels are inserted into. By default it is inserted into the firstlevel.

col_fillobject, default ‘’

If the columns have multiple levels, determines how the otherlevels are named. If None then the index name is repeated.

allow_duplicatesbool, optional, default lib.no_default

Allow duplicate column labels to be created.

Added in version 1.5.0.

namesint, str or 1-dimensional list, default None

Using the given string, rename the DataFrame column which contains theindex data. If the DataFrame has a MultiIndex, this has to be a list ortuple with length equal to the number of levels.

Added in version 1.5.0.

Returns:

DataFrame or None

DataFrame with the new index or None ifinplace=True.

See also

DataFrame.set_index

Opposite of reset_index.

DataFrame.reindex

Change to new indices or expand indices.

DataFrame.reindex_like

Change to same indices as other DataFrame.

Examples

>>>df=pd.DataFrame([('bird',389.0),...('bird',24.0),...('mammal',80.5),...('mammal',np.nan)],...index=['falcon','parrot','lion','monkey'],...columns=('class','max_speed'))>>>df         class  max_speedfalcon    bird      389.0parrot    bird       24.0lion    mammal       80.5monkey  mammal        NaN

When we reset the index, the old index is added as a column, and anew sequential index is used:

>>>df.reset_index()    index   class  max_speed0  falcon    bird      389.01  parrot    bird       24.02    lion  mammal       80.53  monkey  mammal        NaN

We can use thedrop parameter to avoid the old index being added asa column:

>>>df.reset_index(drop=True)    class  max_speed0    bird      389.01    bird       24.02  mammal       80.53  mammal        NaN

You can also usereset_index withMultiIndex.

>>>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)>>>df               speed species                 max    typeclass  namebird   falcon  389.0     fly       parrot   24.0     flymammal lion     80.5     run       monkey    NaN    jump

Using thenames parameter, choose a name for the index column:

>>>df.reset_index(names=['classes','names'])  classes   names  speed species                     max    type0    bird  falcon  389.0     fly1    bird  parrot   24.0     fly2  mammal    lion   80.5     run3  mammal  monkey    NaN    jump

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

>>>df.reset_index(level='class')         class  speed species                  max    typenamefalcon    bird  389.0     flyparrot    bird   24.0     flylion    mammal   80.5     runmonkey  mammal    NaN    jump

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

>>>df.reset_index(level='class',col_level=1)                speed species         class    max    typenamefalcon    bird  389.0     flyparrot    bird   24.0     flylion    mammal   80.5     runmonkey  mammal    NaN    jump

When the index is inserted under another level, we can specify underwhich one with the parametercol_fill:

>>>df.reset_index(level='class',col_level=1,col_fill='species')              species  speed species                class    max    typenamefalcon           bird  389.0     flyparrot           bird   24.0     flylion           mammal   80.5     runmonkey         mammal    NaN    jump

If we specify a nonexistent level forcol_fill, it is created:

>>>df.reset_index(level='class',col_level=1,col_fill='genus')                genus  speed species                class    max    typenamefalcon           bird  389.0     flyparrot           bird   24.0     flylion           mammal   80.5     runmonkey         mammal    NaN    jump