Given a DataFrame, how can I add a new level to the columns based on an iterable given by the user? In other words, how do I append a new level?
The question How to simply add a column level to a pandas dataframe shows how to add a new level given a single value, so it doesn’t cover this case.
Here is the expected behaviour:
>>> df = pd.DataFrame(0, columns=["A", "B"], index=range(2)) >>> df A B 0 0 0 1 0 0 >>> append_level(df, ["C", "D"]) A B C D 0 0 0 1 0 0
The solution should also work with MultiIndex columns, so
>>> append_level(append_level(df, ["C", "D"]), ["E", "F"]) A B C D E F 0 0 0 1 0 0
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Answer
If the columns is not multiindex, you can just do:
df.columns = pd.MultiIndex.from_arrays([df.columns.tolist(), ['C','D']])
If its multiindex:
if isinstance(df.columns, pd.MultiIndex): df.columns = pd.MultiIndex.from_arrays([*df.columns.levels, ['E', 'F']])
The pd.MultiIndex.levels
gives a Frozenlist of level values and you need to unpack to form the list of lists as input to from_arrays