Python

#where A is the name of the column
#where df is the name of the dataframe
count = df["A"].isna().sum()

# to mark NaN column as True
df['your column name'].isnull()

# Check for nan values and store them in dataset named (nan_values)
nan_data = data.isna()
nan_data.head()

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