使用列表推導 Python 將值添加到數組列表的第一個索引

Question

下面的 Vals 列表理解修改了Values ，以便對於第 n 行它索引數組值。 我如何能夠在Vals列表理解中添加一個增量，它在所有修改后的列表前面添加 100？ 我只想修改列表理解 function 來做到這一點。

import numpy as np 

first_index_val = 100
Values = np.array([[130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72],
                  [130,123,135.3,139.05,156.08,163.88,173.72]])

Vals = np.array([arr[i:] for i,arr in enumerate(Values.tolist())])

Output：

[list([130.0, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([135.3, 139.05, 156.08, 163.88, 173.72])
 list([139.05, 156.08, 163.88, 173.72]) list([156.08, 163.88, 173.72])
 list([163.88, 173.72]) list([173.72])]

預期 Output：

[list([100, 130.0, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 123.0, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 135.3, 139.05, 156.08, 163.88, 173.72])
 list([100, 139.05, 156.08, 163.88, 173.72]) list([100, 156.08, 163.88, 173.72])
 list([100, 163.88, 173.72]) list([100, 173.72])]

Answer 1

只需添加到列表理解中。

Vals = np.array([100] + [arr[i:] for i,arr in enumerate(Values.tolist())])

Answer 2

這是我的看法，簡單而明確。

import numpy as np

first_index_val = 100
values = np.array([[130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72],
               [130, 123, 135.3, 139.05, 156.08, 163.88, 173.72]])


flipped = np.flip(values, 1)

appended = np.array([np.append(x, first_index_val) for x in flipped])

print(np.flip(appended, 1))