Assume, you have defined a data frame which has 2 columns.import numpy as npdf = pd.DataFrame({'Id':[1,2,3,4],'val':[2,5,np.nan,6]})Which of the following will be the output of the below print statement?print df.val == np.nan0 False1 False2 False3 False0 False1 False2 True3 False0 True1 True2 True3 TrueNone of these
Question
Assume, you have defined a data frame which has 2 columns.import numpy as npdf = pd.DataFrame({'Id':[1,2,3,4],'val':[2,5,np.nan,6]})Which of the following will be the output of the below print statement?print df.val == np.nan0 False1 False2 False3 False0 False1 False2 True3 False0 True1 True2 True3 TrueNone of these
Solution
The output of the print statement will be:
0 False 1 False 2 False 3 False
This is because np.nan (Not a Number) is a special floating-point value and cannot be compared to other values using the '==' operator. In Python, to check if a value is NaN, we should use the function np.isnan(). So, if we want to check if 'val' is NaN, we should use: print df['val'].isnull().
Therefore, the correct answer is:
0 False 1 False 2 False 3 False
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