[Python] Pandas dont drop level of multindex when getting first value

Example

import pandas as pd
import numpy as np
t=pd.DataFrame({'c1': {(1, 1, 1): 1, (1, 2, 9): 2, (2, 1, 3): np.nan, (2, 1, 7): 4, (4, 2, 2): 6}, 'c2': {(1, 1, 1): 3, (1, 2, 9): 3, (2, 1, 3): 3, (2, 1, 7): 1, (4, 2, 2): 2}})
print(t["c1"].groupby(level=[0,1]).first())


output

1 1 1.0
2 2.0
2 1 4.0
4 2 6.0
Name: c1, dtype: float64


Desired:

1 1 1 1.0
2 9 2.0
2 1 7 4.0
4 2 2 6.0
Name: c1, dtype: float64



Answer doesn't need to be a groupby, I feel like there has to be a way to use a slice on the iloc of an index that respects nans

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