我已经使用pandas和numpy从csv创建了数组。
这是将2D csv转换为3D数组的代码：
>>> import pandas as pd
>>> import numpy as npp
>>> df = pd.read_csv("test.csv")
>>> df_mat = df.values
>>> seq_len = 3
>>> data=[]
>>> for index in range(len(df_mat) - seq_len):
... data.append(df_mat[index: index + seq_len])
...
>>> data = np.array(data)
>>> data.shape
(4, 3, 9)
使用的csv是：
input1,input2,input3,input4,input5,input6,input7,input8,output
1,2,3,4,5,6,7,8,1
2,3,4,5,6,7,8,9,0
3,4,5,6,7,8,9,10,-1
4,5,6,7,8,9,10,11,-1
5,6,7,8,9,10,11,12,1
6,7,8,9,10,11,12,13,0
7,8,9,10,11,12,13,14,1
现在，我想将3D阵列恢复为2D阵列格式。
请让我知道我该怎么做。没有任何线索。
最佳答案
沿每个块在0th行上切片，直到最后一块，并与最后一块堆叠-
np.vstack((data[np.arange(data.shape[0]-1),0],data[-1]))
输出具有给定的样本数据-
In [24]: np.vstack((data[np.arange(data.shape[0]-1),0],data[-1]))
Out[24]:
array([[ 1, 2, 3, 4, 5, 6, 7, 8, 1],
[ 2, 3, 4, 5, 6, 7, 8, 9, 0],
[ 3, 4, 5, 6, 7, 8, 9, 10, -1],
[ 4, 5, 6, 7, 8, 9, 10, 11, -1],
[ 5, 6, 7, 8, 9, 10, 11, 12, 1],
[ 6, 7, 8, 9, 10, 11, 12, 13, 0],
[ 7, 8, 9, 10, 11, 12, 13, 14, 1]], dtype=int64)
或将
0th行切片在所有块上并堆叠，最后一块跳过第一行-In [28]: np.vstack((data[np.arange(data.shape[0]),0],data[-1,1:]))
Out[28]:
array([[ 1, 2, 3, 4, 5, 6, 7, 8, 1],
[ 2, 3, 4, 5, 6, 7, 8, 9, 0],
[ 3, 4, 5, 6, 7, 8, 9, 10, -1],
[ 4, 5, 6, 7, 8, 9, 10, 11, -1],
[ 5, 6, 7, 8, 9, 10, 11, 12, 1],
[ 6, 7, 8, 9, 10, 11, 12, 13, 0],
[ 7, 8, 9, 10, 11, 12, 13, 14, 1]], dtype=int64)