使用列表（由列表组成）创建数组，但不展平内部列表

例1

temp_list_column1=['St. Raphael', 'Goppingen', 'HSG Wetzlar', 'Huttenberg', 'Kiel', 'Stuttgart', 'Izvidac', 'Viborg W', 'Silkeborg-Voel W', 'Bjerringbro W', 'Lyngby W', 'Most W', 'Ostrava W', 'Presov W', 'Slavia Prague W', 'Dicken', 'Elbflorenz', 'Lubeck-Schwartau', 'HK Ogre/Miandum', 'Stal Mielec', 'MKS Perla Lublin W', 'Koscierzyna W', 'CS Madeira W', 'CSM Focsani', 'CSM Bucuresti', 'Constanta', 'Iasi', 'Suceava', 'Timisoara', 'Saratov', 'Alisa Ufa W', 'Pozarevac', 'Nove Zamky', 'Aranas', 'Ricoh', 'H 65 Hoor W', 'Lugi W', 'Strands W'] temp_list_column2=[['32', '16', '16'], ['32', '16', '16'], ['27', '13', '14'], ['23', '9', '14'], ['29', '14', '15'], ['24', '17', '7'], ['30', '15', '15'], ['26', '12', '14'], ['27', '13', '14'], ['26'], ['18', '9', '9'], ['34', '15', '19'], ['30', '13', '17'], ['31', '13', '18'], ['27', '10', '17'], ['28', '14', '14'], ['24', '14', '10'], ['28', '12', '16'], ['28', '9', '19'], ['22', '13', '9'], ['30', '14', '16'], ['22', '14', '8'], ['17', '8', '9'], ['26'], ['41', '21', '20'], ['36', '18', '18'], ['10'], ['25', '12', '13'], ['27', '16', '11'], ['31', '15', '16'], ['25', '15', '10'], ['24', '8', '16'], ['28', '14', '14'], ['24', '13', '11'], ['26', '14', '12'], ['33', '17', '16'], ['26', '12', '14'], ['17', '12', '5']] import numpy as np temp_array = np.column_stack((temp_list_column1,temp_list_column2))

输出

array([['St. Raphael', ['32', '16', '16']], ['Goppingen', ['32', '16', '16']], ['HSG Wetzlar', ['27', '13', '14']], ['Huttenberg', ['23', '9', '14']], ['Kiel', ['29', '14', '15']], ['Stuttgart', ['24', '17', '7']], ['Izvidac', ['30', '15', '15']], ['Viborg W', ['26', '12', '14']], ['Silkeborg-Voel W', ['27', '13', '14']], ['Bjerringbro W', ['26']], ['Lyngby W', ['18', '9', '9']], ['Most W', ['34', '15', '19']], ['Ostrava W', ['30', '13', '17']], ['Presov W', ['31', '13', '18']], ['Slavia Prague W', ['27', '10', '17']], ['Dicken', ['28', '14', '14']], ['Elbflorenz', ['24', '14', '10']], ['Lubeck-Schwartau', ['28', '12', '16']], ['HK Ogre/Miandum', ['28', '9', '19']], ['Stal Mielec', ['22', '13', '9']], ['MKS Perla Lublin W', ['30', '14', '16']], ['Koscierzyna W', ['22', '14', '8']], ['CS Madeira W', ['17', '8', '9']], ['CSM Focsani', ['26']], ['CSM Bucuresti', ['41', '21', '20']], ['Constanta', ['36', '18', '18']], ['Iasi', ['10']], ['Suceava', ['25', '12', '13']], ['Timisoara', ['27', '16', '11']], ['Saratov', ['31', '15', '16']], ['Alisa Ufa W', ['25', '15', '10']], ['Pozarevac', ['24', '8', '16']], ['Nove Zamky', ['28', '14', '14']], ['Aranas', ['24', '13', '11']], ['Ricoh', ['26', '14', '12']], ['H 65 Hoor W', ['33', '17', '16']], ['Lugi W', ['26', '12', '14']], ['Strands W', ['17', '12', '5']]], dtype=object)

例2

temp_list_column1b=['Benidorm', 'Alpla Hard', 'Dubrava', 'Frydek-Mistek', 'Karvina', 'Koprivnice', 'Nove Veseli', 'Vardar', 'Meble Elblag Wojcik', 'Zaglebie', 'Benfica', 'Barros W', 'Juvelis W', 'Assomada W', 'UOR No.2 Moscow', 'Izhevsk W', 'Stavropol W', 'Din. Volgograd W', 'Zvenigorod W', 'Adyif W', 'Crvena zvezda', 'Ribnica', 'Slovan', 'Jeruzalem Ormoz', 'Karlskrona', 'Torslanda W'] temp_list_column2b=[['28', '14', '14'], ['27', '12', '15'], ['24', '13', '11'], ['24', '14', '10'], ['28', '17', '11'], ['30', '16', '14'], ['26', '15', '11'], ['38', '18', '20'], ['24', '13', '11'], ['33', '15', '18'], ['24', '10', '14'], ['18', '11', '7'], ['22', '9', '13'], ['25', '12', '13'], ['19', '11', '8'], ['24', '10', '14'], ['21', '9', '12'], ['18', '10', '8'], ['31', '17', '14'], ['29', '15', '14'], ['26', '14', '12'], ['29', '12', '17'], ['25', '11', '14'], ['33', '19', '14'], ['32', '14', '18'], ['19', '12', '7']] import numpy as np temp_arrayb = np.column_stack((temp_list_column1b,temp_list_column2b))

输出

array([['Benidorm', '28', '14', '14'], ['Alpla Hard', '27', '12', '15'], ['Dubrava', '24', '13', '11'], ['Frydek-Mistek', '24', '14', '10'], ['Karvina', '28', '17', '11'], ['Koprivnice', '30', '16', '14'], ['Nove Veseli', '26', '15', '11'], ['Vardar', '38', '18', '20'], ['Meble Elblag Wojcik', '24', '13', '11'], ['Zaglebie', '33', '15', '18'], ['Benfica', '24', '10', '14'], ['Barros W', '18', '11', '7'], ['Juvelis W', '22', '9', '13'], ['Assomada W', '25', '12', '13'], ['UOR No.2 Moscow', '19', '11', '8'], ['Izhevsk W', '24', '10', '14'], ['Stavropol W', '21', '9', '12'], ['Din. Volgograd W', '18', '10', '8'], ['Zvenigorod W', '31', '17', '14'], ['Adyif W', '29', '15', '14'], ['Crvena zvezda', '26', '14', '12'], ['Ribnica', '29', '12', '17'], ['Slovan', '25', '11', '14'], ['Jeruzalem Ormoz', '33', '19', '14'], ['Karlskrona', '32', '14', '18'], ['Torslanda W', '19', '12', '7']], dtype='<U19')

在第一种情况下，shape是（38，2），而在第二种情况下是（26，4）（我只对列数感兴趣）。我是不是漏掉了什么明显的东西？你知道吗

2条回答

网友
1楼 · 编辑于 2024-06-01 07:52:14

这里的问题似乎是第一个B列表是锯齿状的，而第二个是矩形的。你知道吗
看看Numpy如何将以下两个列表转换为数组的区别（正如@hpaulj指出的，这正是将它们传递给column_stack时发生的情况：
In [1]: b1 = [ ...: [1,2,3], ...: [2,3,4], ...: [3,4,5], ...: [4,5,6]] In [2]: np.array(b1) Out[2]: array([[1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 6]]) In [3]: b2 = [ ...: [1,2,3], ...: [2,3], ...: [3]] In [4]: np.array(b2) Out[4]: array([list([1, 2, 3]), list([2, 3]), list([3])], dtype=object)
因此，当对示例列表进行列堆叠时，在第一种情况下，列表的一维数组将转换为一列，而在第二种情况下，数字的二维矩阵将有3列。你知道吗
您甚至不应该使用Numpy的column_stack在这种情况下，只需将两个列表压缩在一起。如果您想要一个numpy数组作为最终结果，只需np.array(list(zip(list_a, list_b)))
编辑：回顾过去，您的数据结构听起来更像通常所说的数据帧，而不是Numpy试图提供给您的矩阵。你知道吗
import pandas as pd data = pd.DataFrame() data['name'] = temp_list_column1 data['numbers'] = test_list_column2 # Or data = pd.DataFrame(list(zip(temp_list_column1, temp_list_column2)), columns=['name', 'numbers'])
它提供的数据结构如下所示：
name numbers 0 John [1, 2, 3] 1 James [2, 3, 4] 2 Peter [3, 4, 5] 3 Paul [4, 5, 6]

网友
2楼 · 编辑于 2024-06-01 07:52:14

诊断
问题似乎是针对第二个示例，所有子列表都有3个元素，而在第一个示例中，有长度为1的子列表，例如['Bjerringbro W'，['26']]；列表['26']只有一个元素。你知道吗
显然在第二种情况下np.u列堆栈强制不将列表作为单元格元素。事实上，我们可以有另一个讨论，为什么你想把列表看作单元格元素，我在这里不讨论。这是解决办法
特例解决方案
我想你不介意用熊猫吧
import pandas as pd series_1 = pd.Series(temp_list_column1b).to_frame(name='col1') # name it whatever you want series_2 = pd.Series(temp_list_column2b).to_frame(name='col2') # name it whatever you want df = pd.concat([series_1, series_2], axis=1) # print(df) # view in pandas form # print(df.values) # to see how it looks like as a numpy array # print(df.values.shape) # to see how what the shape is in terms of numpy
广义解
假设您有一个这样的列的列表，称为“列的列表”。然后：
import pandas as pd ''' list_of_cols: all the lists you want to combine ''' df = pd.concat([pd.Series(temp_col).to_frame() for temp_col in list_of_cols], axis=1)
我希望这有帮助！你知道吗

例1

例2

诊断

特例解决方案

广义解

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