data_in_window = self.data.iloc[i:i+window_length, column_idxs]什么意思
时间: 2024-04-04 19:32:26 浏览: 13
这行代码是从self.data中根据指定的窗口大小和列索引号,选取一部分数据进行处理。具体来说,iloc是pandas中的一种索引方式,它根据位置选择行和列,其中i:i+window_length表示选取从第i行开始,连续window_length行的数据,column_idxs则是列索引号列表,表示选取列索引号在该列表中的所有列。因此,这行代码的作用是在self.data中选取从i行开始,连续window_length行以及列索引号在column_idxs列表中的所有列,将其存储在data_in_window中。
相关问题
优化这段代码 x_train_YS, y_train_YS = data.iloc[0:418+20*i,list(range(0))+list(range(8,95))],data.iloc[0:418+20*i,95] x_test_YS, y_test_YS = data.iloc[418+20*i:438+20*i,list(range(0))+list(range(8,95))],data.iloc[418+20*i:438+20*i,95] x_train_YS_1,y_train_YS_1 = x_train_YS.iloc[1:418+20*i,1:87].values,y_train_YS.iloc[1:418+20*i,87].values x_test_YS_1,y_test_YS_1 = x_test_YS.iloc[418+20*i:438+20*i,1:87].values,y_test_YS.iloc[418+20*i:438+20*i,87].values
可以对这段代码进行如下优化:
```
start = 0
end = 418 + 20 * i
cols = list(range(0)) + list(range(8, 95))
x_train_YS = data.iloc[start:end, cols]
y_train_YS = data.iloc[start:end, 95]
start = 418 + 20 * i
end = 438 + 20 * i
x_test_YS = data.iloc[start:end, cols]
y_test_YS = data.iloc[start:end, 95]
cols_1 = list(range(1, 87))
x_train_YS_1 = x_train_YS.iloc[1:end-1, cols_1].values
y_train_YS_1 = y_train_YS.iloc[1:end-1].values
x_test_YS_1 = x_test_YS.iloc[:, cols_1].values
y_test_YS_1 = y_test_YS.iloc[:, -1].values
```
这样,我们可以避免重复代码,减少重复计算,提高代码的可读性和可维护性。同时,将计算结果存储在变量中,可以提高代码的执行效率。
优化这段代码for i in range(14): x_train_YS, y_train_YS = data.iloc[0:418+20*i,list(range(0))+list(range(8,95))],data.iloc[0:418+20*i,95] x_test_YS, y_test_YS = data.iloc[418+20*i:438+20*i,list(range(0))+list(range(8,95))],data.iloc[418+20*i:438+20*i,95] x_train_YS_1,y_train_YS_1 = x_train_YS.iloc[1:418+20*i,1:87].values,y_train_YS.iloc[1:418+20*i,87].values x_test_YS_1,y_test_YS_1 = x_test_YS.iloc[418+20*i:438+20*i,1:87].values,y_test_YS.iloc[418+20*i:438+20*i,87].values
可以对这段代码进行如下优化:
```
start = 0
end = 418
cols = list(range(0)) + list(range(8, 95))
cols_1 = list(range(1, 87))
train_data = []
test_data = []
for i in range(14):
x_train_YS, y_train_YS = data.iloc[start:end, cols], data.iloc[start:end, 95]
x_test_YS, y_test_YS = data.iloc[start+418:end+438, cols], data.iloc[start+418:end+438, 95]
x_train_YS_1, y_train_YS_1 = x_train_YS.iloc[1:end-1, cols_1].values, y_train_YS.iloc[1:end-1].values
x_test_YS_1, y_test_YS_1 = x_test_YS.iloc[:, cols_1].values, y_test_YS.iloc[:, -1].values
train_data.append((x_train_YS_1, y_train_YS_1))
test_data.append((x_test_YS_1, y_test_YS_1))
start = end
end += 20 * (i + 2)
```
这样,我们可以将数据处理部分的代码放入循环中,避免了重复代码,同时将结果存储在列表中,便于后续处理。