回答編集履歴
2
結局追記
answer
CHANGED
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@@ -39,4 +39,37 @@
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39
39
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B = np.r_[B, A1]
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40
40
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41
41
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print((B.T).shape) # ②(492, 2)だが正解は？
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42
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+
```
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43
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+
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44
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+
結局は
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45
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---
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46
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+
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47
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+
かなり推測（エスパー）入っていますが、以下が求めるコードになるかと思われます。
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48
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```Python
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49
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import pandas as pd
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50
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import numpy as np
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51
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52
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dat = np.arange(164*14).reshape(164,-1)
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53
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L5 = ['W-A0', 'W-B0', 'W-F0', 'W-C1', 'W-E1', 'W-A2', 'W-B2', 'W-D2', 'W-F2', 'W-C3', 'W-E3',
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'W-A4', 'W-B4', 'W-F4']
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55
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56
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Ds1 = pd.DataFrame(dat,columns=L5)
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Ds2 = pd.DataFrame(dat,columns=L5)
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58
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print(Ds1.shape,Ds2.shape) # 質問文よりどちらも(164, 14) (164, 14)
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59
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60
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dL = list(range(100, 2100, 200)) # [100,300,500,...]
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61
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#B = np.zeros((0, Ds1.values.shape[0])) # 不要
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62
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63
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for i in range(0,2):
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64
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# Df1とDf2の'W=??'列 同士（＋dL）を足し合わせる shape(164,xx) xx=3,2
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65
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col1 = Ds1.columns.str.contains(r'(?=.*W)(?=.*%s)' % i)
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66
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col2 = Ds2.columns.str.contains(r'(?=.*W)(?=.*%s)' % i)
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67
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A1 = dL[i] + Ds2.loc[:, col2].values + Ds1.loc[:, col1].values
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68
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if i == 0:
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70
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B = A1.copy()
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71
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else:
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72
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B = np.c_[B, A1] # 列方向に足す！
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73
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+
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74
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print(B.shape) # 欲しいshapeは(164, 5)
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42
75
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```
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1
コード修正
answer
CHANGED
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@@ -2,16 +2,18 @@
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2
2
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そのままでは無理なので[numpy.resize](https://docs.scipy.org/doc/numpy-1.15.1/reference/generated/numpy.resize.html)で足りない方の列を０埋めで増やしてやるしかないと思います。
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3
3
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参考：[Python: Resize an existing array and fill with zeros](https://stackoverflow.com/questions/9251635/python-resize-an-existing-array-and-fill-with-zeros)
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4
4
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5
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なお、２点ほど疑問点をコメント中に記載しましたので回答願います。
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5
6
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```Python
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6
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import pandas as pd
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7
8
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import numpy as np
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8
9
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9
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-
dat = np.arange(
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10
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dat = np.arange(164*14).reshape(164,-1)
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10
11
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L5 = ['W-A0', 'W-B0', 'W-F0', 'W-C1', 'W-E1', 'W-A2', 'W-B2', 'W-D2', 'W-F2', 'W-C3', 'W-E3',
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'W-A4', 'W-B4', 'W-F4']
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13
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Ds1 = pd.DataFrame(dat,columns=L5)
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14
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Ds2 = pd.DataFrame(dat,columns=L5)
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16
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print(Ds1.shape,Ds2.shape) # 質問文よりどちらも(164, 14) (164, 14)
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15
17
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16
18
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dL = list(range(100, 2100, 200))
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19
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#B = np.zeros((0, Ds1.values.shape[0])) # 不要
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@@ -20,20 +22,21 @@
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col1 = Ds1.columns.str.contains(r'(?=.*W)(?=.*%s)' % i)
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col2 = Ds2.columns.str.contains(r'(?=.*W)(?=.*%s)' % i)
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A1 = dL[i] + Ds2.loc[:, col2].values + Ds1.loc[:, col1].values
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23
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-
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25
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+
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# copy()が必要
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# Numpy, the array doesn't have its own data?
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# https://stackoverflow.com/questions/23253144/numpy-the-array-doesnt-have-its-own-data
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27
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-
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29
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A1 = A1.reshape(1, -1).copy()
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30
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print(A1.shape) # ①i=0で(1, 492)、i=1で(1, 328)だが正しいか？
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28
31
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29
32
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if i == 0:
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30
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-
B =
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33
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+
B = A1.copy()
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31
34
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else: # 列数を大きい方に合わせる
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32
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-
if B.shape[1] <
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35
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+
if B.shape[1] < A1.shape[1]:
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33
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-
B.resize((B.shape[0],
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36
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B.resize((B.shape[0],A1.shape[1]))
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34
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-
elif
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37
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+
elif A1.shape[1] < B.shape[1]:
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35
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-
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38
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+
A1.resize((1,B.shape[1]))
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36
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-
B = np.r_[B,
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39
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+
B = np.r_[B, A1]
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37
40
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38
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-
print(B.T)
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41
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+
print((B.T).shape) # ②(492, 2)だが正解は？
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39
42
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```
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