Pandas DataFrame | rename_axis method
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Pandas's DataFrame.rename_axis(~) method modifies the axis labels.
The method rename_axis(~) does not change the row or column labels, but instead changes the axis label. If you want to change row or column labels, use DataFrame.rename(~) instead.
Parameters
1. mapper | scalar or array-like | optional
The new name assigned to the specified axis.
2. index | scalar or array-like or dict-like or function | optional
A dictionary whose keys are the index names you want to modify, and values are the new index names.
3. columns | scalar or array-like or dict-like or function | optional
A dictionary whose keys are the column names you want to modify, and values are the new column names.
4. axis | boolean or string | optional
Whether or not to rename the rows or columns:
Axis | Description |
|---|---|
| Renaming row index. |
| Renaming column axis. |
By default, axis=0.
Opt to use index or columns over mapper and axis for readability. See examples below for clarification.
5. copy | boolean | optional
Whether or not to return a new DataFrame without modifying the source DataFrame. By default, copy=True.
6. inplace | boolean | optional
Whether or not to perform the renaming in place:
If
True, then the source DataFrame will be directly modified, and no new DataFrame will be created.If
False, then a new DataFrame is created and returned.
By default, inplace=False.
Return Value
A DataFrame with a new name for one of its axes. Note that if inplace=True, then nothing is returned since the source DataFrame is directly modified.
Examples
Consider the following DataFrame:
df
A Ba 3 5b 4 6
Our df currently does not have an axis label.
Renaming the axis label
To give df an axis label:
df.rename_axis(columns=["C"])
C A Ba 3 5b 4 6
Here, our index (i.e. row labels) are assigned the name "C".
Equivalently, we could have used the mapper and axis parameters:
df.rename_axis(mapper="C", axis=1) # This way is not preferred.
C A Ba 3 5b 4 6
