Parse Pandas (multi)index To Datetime

I have multi-index df as follows x y id date abc 3/1/1994 100 7 9/1/1994 90 8 3/1/1995 80 9 Where dates are stored as str. I want to

Solution 1:

As mentioned, you have to recreate the index:

df.index = df.index.set_levels([df.index.levels[0], pd.to_datetime(df.index.levels[1])])

Solution 2:

You cannot modify it in-place. You can use pandas.MultiIndex.map to create a new index and then assign it:

new_tuples = df.index.map(lambda x: (x[0], pd.to_datetime(x[1])))
df.index = pd.MultiIndex.from_tuples(new_tuples, names=["id", "date"])

Solution 3:

One cannot modify MultiIndex in-place, so we have to recreate it. To do so, we use get_level_values to obtain multiindex levels as Series, then apply pd.to_datefime, then reconstruct multiindex from two levels.

index = pd.MultiIndex.from_tuples([('abc', '3/1/1994'), ('abc', '9/1/1994')],
                                 names=('id', 'date'))
df = pd.DataFrame({'x': [1, 2]}, index=index)
print(df.index.get_level_values(level=1).dtype)
# object

df.index = pd.MultiIndex.from_arrays([index.get_level_values(level=0),
                                      pd.to_datetime(
                                          index.get_level_values(level=1))])
print(df.index.get_level_values(level=1).dtype)
# datetime64[ns]