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 value in dataframe python
# to mark NaN column as True
df['your column name'].isnull()
count rows with nan pandas
np.count_nonzero(df.isnull().values)
np.count_nonzero(df.isnull()) # also works
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