Return dataframe subset based on a list of boolean values

You can use masking here:

df[np.array([0,1,0,0,1,1,0,0,0,1],dtype=bool)]

So we construct a boolean array with true and false. Every place where the array is True is a row we select.

Mind that we do not filter inplace. In order to retrieve the result, you have to assign the result to an (optionally different) variable:

df2 = df[np.array([0,1,0,0,1,1,0,0,0,1],dtype=bool)]

Convert the list to a boolean array and then use boolean indexing:

df = pd.DataFrame(np.random.randint(10, size=(10, 3)))

df[np.array(lst).astype(bool)]
Out: 
   0  1  2
1  8  6  3
4  2  7  3
5  7  2  3
9  1  3  4

Related