Pandas DataFrame rename() Method
Example
Rename the row indexes of the DataFrame:
import pandas as pd
data = {
"age": [50, 40, 30],
"qualified":
[True, False, False]
}
idx = ["Sally", "Mary", "John"]
df =
pd.DataFrame(data, index=idx)
newdf = df.rename({"Sally": "Pete",
"Mary": "Patrick", "John": "Paula"})
print(newdf)
Try it Yourself »
Definition and Usage
The rename()
method allows you to change
the row indexes, and the columns labels.
Syntax
dataframe.rename(mapper, index, columns, axis, copy,
inplace, level, errors)
Parameters
The index
, columns
,
axis
,
copy
,
inplace
,
level
,
errors
parameters are
keyword arguments.
Parameter | Value | Description |
---|---|---|
mapper | Optional. A dictionary where the old index/label is the key and the new index/label is the value | |
index | old and new indexes as key/value pairs | Optional. A dictionary where the old index is the key and the new index is the value |
columns | old and new labels as key/value pairs | Optional. A dictionary where the old label is the key and the new label is the value |
axis | 0 |
Optional, default 0. The axis to perform the renaming (important if the mapper parameter is present and index or columns are not) |
copy | True |
Optional, default True. Whether to also copy underlying data or not |
inplace | True |
Optional, default False. If True: the operation is done on the current DataFrame. If False: returns a copy where the operation is done. |
level | Number Label |
Optional, specifies which level to rename when working with MultiIndex DataFrames |
errors | 'ignore' |
Optional, default 'ignore'. Specifies whether or not to return an error if no such index/label is present in the DataFrame |
Return Value
A DataFrame with the result, or None if the inplace parameter is set to True.
This function does NOT make changes to the original DataFrame object.