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pandas Missing Data, NaN and NA, what does print(s.sum()) print after s = pd.Series([1, 2, None])?
Block 3, Missing Data, NaN and NA, question 6 of the pandas sample
import pandas as pd
s = pd.Series([1, 2, None])
print(s.sum())What does this print?
Show the answer and why each option is right or wrong
Answer, C. 3.0
- A. 2.0
- Drops one of the two real values along with the missing one.
- B. 3
- Assumes the result stays a plain integer even though the series holding it became float once a missing value was introduced.
- C. 3.0
- Correct. sum() skips missing values by default, so it adds 1 and 2, and the result prints as 3.0 because the series became float the moment None entered it.
- D. nan
- Assumes a single missing value forces the whole sum to come back missing, the way it would with skipna turned off.
By default, sum(), mean() and most other reductions in pandas ignore missing values rather than propagating them. The dtype of the series is decided when it is built, not when it is summed, so a series that became float because of a None still reports its sum as a float.
The answer above is what pandas 3.0.5 printed when the snippet was run, not what someone expected it to do.
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