Python Pandas find all rows where all values are NaN

Question

So I have a dataframe with 5 columns. I would like to pull the indices where all of the columns are NaN. I was using this code:

nan = pd.isnull(df.all)

but that is just returning false because it is logically saying no not all values in the dataframe are null. There are thousands of entries so I would prefer to not have to loop through and check each entry. Thanks!

Asked By: Steven Setteducati Jr.

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Source

Answer 1

It should just be:

df.isnull().all(1)

The index can be accessed like:

df.index[df.isnull().all(1)]

Demonstration

np.random.seed([3,1415])
df = pd.DataFrame(np.random.choice((1, np.nan), (10, 2)))
df

idx = df.index[df.isnull().all(1)]
nans = df.ix[idx]
nans

Timing

code

np.random.seed([3,1415])
df = pd.DataFrame(np.random.choice((1, np.nan), (10000, 5)))

Answered By: piRSquared

Answer 2

Assuming your dataframe is named df, you can use boolean indexing to check if all columns (axis=1) are null. Then take the index of the result.

np.random.seed(0)
df = pd.DataFrame(np.random.randn(5, 3))
df.iloc[-2:, :] = np.nan
>>> df
          0         1         2
0  1.764052  0.400157  0.978738
1  2.240893  1.867558 -0.977278
2  0.950088 -0.151357 -0.103219
3       NaN       NaN       NaN
4       NaN       NaN       NaN

nan = df[df.isnull().all(axis=1)].index

>>> nan
Int64Index([3, 4], dtype='int64')

Answered By: Alexander

Answer 3

From the master himself: https://stackoverflow.com/a/14033137/6664393

nans = pd.isnull(df).all(1).nonzero()[0]

Answered By: user357269

Python Pandas find all rows where all values are NaN

Question:

Answers:

Demonstration

Timing