Python NP.round解算数据后NP.unique

这是因为您的收件箱为float32，而numpy中的默认数字格式为float64.因此，float 32中四舍五入的数字在float 64中不会明显四舍五入，因为数字表示方式有点不同. 解决方案是将输入数组转换为float 64或将结果_数组转换为float 32.

Solution 1

将numpy数组转换为float 32:

rounded_data = data_with_target_label.round(decimals=2)

unique_values, counts = np.unique(rounded_data, return_counts=True)
result_array = np.column_stack((unique_values, counts))

result_array = np.float32(result_array)

Solution 2

转换输入数据.例如，输入是pd.DataFrame(或pd.Series):

df = pd.DataFrame({'vals': np.array([0.013242, 
                                     3.94099998, 
                                     9.99999978, 
                                     0.03234, 
                                     0.05532, 
                                     33.22, 
                                     33.44, 
                                     55.66])}, dtype = 'float32')


rounded_data = df['vals'].astype('float64').round(decimals=2)

unique_values, counts = np.unique(rounded_data, return_counts=True)

result_array = np.column_stack((unique_values, counts))