Python, Pandas : Return only those rows which have missing values

While working in Pandas in Python...

I'm working with a dataset that contains some missing values, and I'd like to return a dataframe which contains only those rows which have missing data. Is there a nice way to do this?

(My current method to do this is an inefficient "look to see what index isn't in the dataframe without the missing values, then make a df out of those indices.")

You can use any axis=1 to check for least one True per row, then filter with boolean indexing:

null_data = df[df.isnull().any(axis=1)]

df.isnull().any(axis = 1).sum()

this gives you the total number of rows with at least one missing data