Branch-AI

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This question is validated if the text file has successfully been loaded in a NumPy array with genfromtxt('winequality-red.csv', delimiter=',') and the reduced arrays weights 76800 bytes
This question is validated if the output is

array([[ 7.4   ,  0.7   ,  0.    ,  1.9   ,  0.076 , 11.    , 34.    ,
        0.9978,  3.51  ,  0.56  ,  9.4   ,  5.    ],
      [ 7.4   ,  0.66  ,  0.    ,  1.8   ,  0.075 , 13.    , 40.    ,
        0.9978,  3.51  ,  0.56  ,  9.4   ,  5.    ],
      [ 6.7   ,  0.58  ,  0.08  ,  1.8   ,  0.097 , 15.    , 65.    ,
        0.9959,  3.28  ,  0.54  ,  9.2   ,  5.    ]])

This slicing gives the answer my_data[[1,6,11],:].

This question is validated if the answer if False. There many ways to get the answer: find the maximum or check values greater than 20.
This question is validated if the answer is 10.422983114446529.
This question is validated if the answers is:
```
pH stats
25 percentile:  3.21
50 percentile:  3.31
75 percentile:  3.4
mean:  3.3111131957473416
min:  2.74
max:  4.01
```
Note: Using percentile or median may give different results depending on the duplicate values in the column. If you do not have my results please use percentile.
This question is validated if the answer is ~5.2. The first step is to get the percentile 20% of the column sulphates, then create a boolean array that contains True of the value is smaller than the percentile 20%, then select this rows with the column quality and compute the mean.
This question is validated if the output for the best wines is:

array([ 8.56666667,  0.42333333,  0.39111111,  2.57777778,  0.06844444,
    13.27777778, 33.44444444,  0.99521222,  3.26722222,  0.76777778,
    12.09444444,  8.        ])

And the output for the bad wines is:

array([ 8.36    ,  0.8845  ,  0.171   ,  2.635   ,  0.1225  , 11.      ,
    24.9     ,  0.997464,  3.398   ,  0.57    ,  9.955   ,  3.      ])

This can be done in three steps: Get the max, create a boolean mask that indicates rows with max quality, use this mask to subset the rows with the best quality and compute the mean on the axis 0.

2.2 KiB Raw Blame History

2.2 KiB

Raw Blame History