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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.

Solution

  • 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()

    enter image description here

    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.