Question

我想将numpy数组转换为5类：非常低，低，平均，高，非常高;根据值是-2还是更高标准。 dev远离阵列的平均值（非常低）; -1 std。 dev或更远离平均值（低级别）;介于-1和+1之间。偏离平均值（平均值）;介于+1和+2之间。 dev from mean（高级）和大于+2 std。开发。从平均值（非常高级）。

我尝试过使用stats.perentileofscore，但这并没有给我我想要的东西：

arr = np.random.rand(100)
[stats.percentileofscore(x, a, 'rank') for a in arr]

Answer 1

您可以在Pandas中使用pd.cut。

sd = arr.std()
m = arr.mean()
>>> pd.cut(arr, [m - sd* 10000, m - sd * 2, m - sd, m + sd, m + sd *2, m + sd* 10000])
[(0.204, 0.785], (0.204, 0.785], (0.785, 1.0764], (0.785, 1.0764], (0.204, 0.785], ..., (0.204, 0.785], (0.204, 0.785], (-0.0875, 0.204], (0.204, 0.785], (0.785, 1.0764]]
Length: 100
Categories (5, object): [(-2909.105, -0.0875] < (-0.0875, 0.204] < (0.204, 0.785] < (0.785, 1.0764] < (1.0764, 2910.0944]]

重命名您的类别：

buckets = (pd.Categorical(pd.cut(arr, 
               [m - sd * 10000, m - sd * 2, m - sd, m + sd, m + sd * 2, m + sd * 10000]))
           .rename_categories(['very low', 'low', 'average', 'high', 'very high']))

>>> buckets
[average, average, high, high, average, ..., average, average, low, average, high]
Length: 100
Categories (5, object): [very low, low, average, high, very high]

将numpy数组转换为类别

1 个答案: