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

Question

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.")

Answer 1

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)]

Answer 2

Similar to metersk's answer,

null_data = df[np.logical_or.reduce(df.isnull().values, axis=1)]

Test

n = 2
df = pd.DataFrame({'a':np.tile([0,1,2,3,4,np.nan],n),
                   'b':np.tile([0,1,2,3,np.nan,5],n)})

x = df[np.logical_or.reduce(df.isnull().values,axis=1)]
y = df[df.isnull().any(axis=1)]
x.equals(y)