Python 如何通过逐行添加numpy数组来创建数据帧

Python 如何通过逐行添加numpy数组来创建数据帧,python,pandas,Python,Pandas,所以我得到了一堆流式阵列,我想将它们附加到数据帧中。我试着做如下的事情 df = pd.DataFrame(columns=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'y']) outputs = get_outputs() for xp, yp in zip(outputs, labels): ex = np.append(xp, yp) print(ex) print(ex.shape)

所以我得到了一堆流式阵列,我想将它们附加到数据帧中。我试着做如下的事情

df = pd.DataFrame(columns=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'y'])

outputs = get_outputs()

for xp, yp in zip(outputs, labels):
     ex = np.append(xp, yp)
     print(ex)
     print(ex.shape)
     #trying here to create row-dataframe
     exdf = pd.DataFrame(ex, columns=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'y']) 
     #want to append the row to the main dataframe
     df.append(exdf) 
我得到的输出和错误如下

[  4.49039745  -9.63315201   7.70181465 -15.19582367  12.6580925
  -1.17788887  -5.21339655   2.6664052    2.96283174   1.22973883
   6.        ]
(11,)
...
ValueError: Shape of passed values is (11, 1), indices imply (11, 11)
我该怎么做

编辑: 在回答中加入变化后

exdf = pd.DataFrame([ex], columns=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'y'])
print(exdf)
df.append(exdf)
print(df[:1])
我收到空的数据帧

Out
          1         2         3          4  ...         8         9        10    y
0  4.490397 -9.633152  7.701815 -15.195824  ...  2.666405  2.962832  1.229739  6.0

[1 rows x 11 columns]
Empty DataFrame
Columns: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, y]
Index: []

在for循环中添加
[]

 for xp, yp in zip(outputs, labels):
 ex = np.append(xp, yp)
 print(ex)
 print(ex.shape)
 #trying here to create row-dataframe
 exdf = pd.DataFrame([ex], columns=['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'y']) 
 #want to append the row to the main dataframe
 df=df.append(exdf) 

我更新了我的帖子。现在由于某种原因,dataframe是empty@YohanRoth请尝试
pd.DataFrame(例如[:,None],columns=['1','2','3','4','5','6','7','8','9','10','y'])
@YohanRoth同样,您需要将其重新分配
df=df.append(…)
,pandas中的append与python中列表的append不同,我们需要将其重新分配