Write a function rainy_days (rainfall) which takes a nested list rainfall (type is NumPy array). Then,...

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Write a function rainy_days (rainfall) which takes a nested list rainfall (type is NumPy array). Then, the function returns the week with the lowest rainfall observed. Week index starts from 0 (i.e., the first row is week 0, the second row is week 1 etc.). If the week's data does not contain each day's information (i.e., some data missing or extra days added), then that week's data is ignored wholly (but it is still counted as a week). If there are no valid weeks (all weekly measures are invalid), then the function returns -1. You can assume all values in the NumPy array are numbers. You can also assume no two weeks will have to same average rainfalls. For example: Test rainfall = np.array([ [0.2, 0.0, 1.6, 4.8, 9.0, 1.2, 1.4), [3.6, 2.2, 0.0, 0.2, 3.0, 0.3, 1.3], #week 1 total 18.2. #week 2 total 10.6 [0.2, 0.4, 0.9, 0.0, 1.5, 0.0, 1.6 1, #week 3 total 4.6 dtype=object) print (rainy_days (rainfall)) rainfall = np.array( [ [0.2, 0.0, 1.6, 4.8, 0.0, 1.2], [0.2, 0.4, 0.9, 0.0, 1.5, 0.0, 1.6, 0.41 ], dtype=object) #all weeks are invalid measurements, so return -1 print (rainy_days (rainfall)) Result 2 -1 Write a function rainy_days (rainfall) which takes a nested list rainfall (type is NumPy array). Then, the function returns the week with the lowest rainfall observed. Week index starts from 0 (i.e., the first row is week 0, the second row is week 1 etc.). If the week's data does not contain each day's information (i.e., some data missing or extra days added), then that week's data is ignored wholly (but it is still counted as a week). If there are no valid weeks (all weekly measures are invalid), then the function returns -1. You can assume all values in the NumPy array are numbers. You can also assume no two weeks will have to same average rainfalls. For example: Test rainfall = np.array([ [0.2, 0.0, 1.6, 4.8, 9.0, 1.2, 1.4), [3.6, 2.2, 0.0, 0.2, 3.0, 0.3, 1.3], #week 1 total 18.2. #week 2 total 10.6 [0.2, 0.4, 0.9, 0.0, 1.5, 0.0, 1.6 1, #week 3 total 4.6 dtype=object) print (rainy_days (rainfall)) rainfall = np.array( [ [0.2, 0.0, 1.6, 4.8, 0.0, 1.2], [0.2, 0.4, 0.9, 0.0, 1.5, 0.0, 1.6, 0.41 ], dtype=object) #all weeks are invalid measurements, so return -1 print (rainy_days (rainfall)) Result 2 -1

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Below is a Python function that meets the specified requirements import numpy as np def rainydaysrai... View the full answer