pandas.DataFrame.rename#

DataFrame.rename(mapper=None,*,index=None,columns=None,axis=None,copy=None,inplace=False,level=None,errors='ignore')[source]#

Rename columns or index labels.

Function / dict values must be unique (1-to-1). Labels not contained ina dict / Series will be left as-is. Extra labels listed don’t throw anerror.

See theuser guide for more.

Parameters:

mapperdict-like or function

Dict-like or function transformations to apply tothat axis’ values. Use eithermapper andaxis tospecify the axis to target withmapper, orindex andcolumns.

indexdict-like or function

Alternative to specifying axis (mapper,axis=0is equivalent toindex=mapper).

columnsdict-like or function

Alternative to specifying axis (mapper,axis=1is equivalent tocolumns=mapper).

axis{0 or ‘index’, 1 or ‘columns’}, default 0

Axis to target withmapper. Can be either the axis name(‘index’, ‘columns’) or number (0, 1). The default is ‘index’.

copybool, default True

Also copy underlying data.

Note

Thecopy keyword will change behavior in pandas 3.0.Copy-on-Writewill be enabled by default, which means that all methods with acopy keyword will use a lazy copy mechanism to defer the copy andignore thecopy keyword. Thecopy keyword will be removed in afuture version of pandas.

You can already get the future behavior and improvements throughenabling copy on writepd.options.mode.copy_on_write=True

inplacebool, default False

Whether to modify the DataFrame rather than creating a new one.If True then value of copy is ignored.

levelint or level name, default None

In case of a MultiIndex, only rename labels in the specifiedlevel.

errors{‘ignore’, ‘raise’}, default ‘ignore’

If ‘raise’, raise aKeyError when a dict-likemapper,index,orcolumns contains labels that are not present in the Indexbeing transformed.If ‘ignore’, existing keys will be renamed and extra keys will beignored.

Returns:

DataFrame or None

DataFrame with the renamed axis labels or None ifinplace=True.

Raises:

KeyError

If any of the labels is not found in the selected axis and“errors=’raise’”.

See also

DataFrame.rename_axis

Set the name of the axis.

Examples

DataFrame.rename supports two calling conventions

• (index=index_mapper,columns=columns_mapper,...)

• (mapper,axis={'index','columns'},...)

Wehighly recommend using keyword arguments to clarify yourintent.

Rename columns using a mapping:

>>>df=pd.DataFrame({"A":[1,2,3],"B":[4,5,6]})>>>df.rename(columns={"A":"a","B":"c"})   a  c0  1  41  2  52  3  6

Rename index using a mapping:

>>>df.rename(index={0:"x",1:"y",2:"z"})   A  Bx  1  4y  2  5z  3  6

Cast index labels to a different type:

>>>df.indexRangeIndex(start=0, stop=3, step=1)>>>df.rename(index=str).indexIndex(['0', '1', '2'], dtype='object')

>>>df.rename(columns={"A":"a","B":"b","C":"c"},errors="raise")Traceback (most recent call last):KeyError:['C'] not found in axis

Using axis-style parameters:

>>>df.rename(str.lower,axis='columns')   a  b0  1  41  2  52  3  6

>>>df.rename({1:2,2:4},axis='index')   A  B0  1  42  2  54  3  6