Changing a specific column name in pandas DataFrame
Since inplace
argument is available, you don't need to copy and assign the original data frame back to itself, but do as follows:
df.rename(columns={'two':'new_name'}, inplace=True)
A one liner does exist:
In [27]: df=df.rename(columns = {'two':'new_name'})
In [28]: df
Out[28]:
one three new_name
0 1 a 9
1 2 b 8
2 3 c 7
3 4 d 6
4 5 e 5
Following is the docstring for the rename
method.
Definition: df.rename(self, index=None, columns=None, copy=True, inplace=False) Docstring: Alter index and / or columns using input function or functions. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Parameters ---------- index : dict-like or function, optional Transformation to apply to index values columns : dict-like or function, optional Transformation to apply to column values copy : boolean, default True Also copy underlying data inplace : boolean, default False Whether to return a new DataFrame. If True then value of copy is ignored. See also -------- Series.rename Returns ------- renamed : DataFrame (new object)
What about?
df.columns[2] = "new_name"