How to check if any value is NaN in a Pandas DataFrame

How do I check whether a pandas DataFrame has NaN values?

I know about pd.isnan but it returns a DataFrame of booleans. I also found this post but it doesn't exactly answer my question either.

jwilner's response is spot on. I was exploring to see if there's a faster option, since in my experience, summing flat arrays is (strangely) faster than counting. This code seems faster:
df.isnull().values.any()


import numpy as np
import pandas as pd
import perfplot

def setup(n):
df = pd.DataFrame(np.random.randn(n))
df[df > 0.9] = np.nan
return df

def isnull_any(df):
return df.isnull().any()

def isnull_values_sum(df):
return df.isnull().values.sum() > 0

def isnull_sum(df):
return df.isnull().sum() > 0

def isnull_values_any(df):
return df.isnull().values.any()

perfplot.save(
"out.png",
setup=setup,
kernels=[isnull_any, isnull_values_sum, isnull_sum, isnull_values_any],
n_range=[2 ** k for k in range(25)],
)


df.isnull().sum().sum() is a bit slower, but of course, has additional information -- the number of NaNs.

Stack Overflow Q#29530232, score: 892