dataframe find nan rows
df[df.isnull().any(axis=1)]
dataframe find nan rows
df[df.isnull().any(axis=1)]
count nan pandas
#Python, pandas
#Count missing values for each column of the dataframe df
df.isnull().sum()
find nan values in a column pandas
df['your column name'].isnull().sum()
to detect if a data frame has nan values
df.isnull().sum().sum()
5
to detect if a data frame has nan values
> df.isnull().any().any()
True
check if a value is nan pandas
import numpy as np
import pandas as pd
val = np.nan
print(pd.isnull(val))
# True
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