回答編集履歴
3
また見直し
answer
CHANGED
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@@ -11,4 +11,16 @@
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11
11
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# 1 10012 Rice 1500
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12
12
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# 4 10015 Egg 1000
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13
13
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# 5 10016 Tea 1000
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14
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+
```
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15
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+
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16
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+
---
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17
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+
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18
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+
こっちのほうがいいかも
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19
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+
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20
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+
```Python
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21
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is_ticket = df.loc[:, 'PName'].str.startswith('TicketNo-').to_numpy()
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22
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is_remove_pcode = df.loc[:, 'PCode'].to_numpy() == 10011
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23
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24
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cond = np.r_[False, (is_ticket[:-1] & is_remove_pcode[1:]), False]
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25
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res = df.loc[~(cond[1:] | cond[:-1])]
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14
26
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```
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2
抜けてた！
answer
CHANGED
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@@ -2,7 +2,7 @@
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2
2
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is_ticket = df['PName'].str.startswith('TicketNo-').to_numpy()
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3
3
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is_remove_pcode = df['PCode'].to_numpy() == 10011
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4
4
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5
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-
drop_index = np.all([is_ticket, np.concatenate((is_remove_pcode[1:], is_remove_pcode[-1:]))], 0)
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5
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drop_index = np.all([is_ticket, np.concatenate((is_remove_pcode[1:], is_remove_pcode[-1:]))], 0).nonzero()[0]
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6
6
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res = df.drop([*drop_index, *(drop_index+1)])
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7
7
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8
8
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print(res)
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1
to_numpy利用
answer
CHANGED
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@@ -1,9 +1,9 @@
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1
1
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```Python
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2
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-
is_ticket = df['PName'].str.startswith('TicketNo-')
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2
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+
is_ticket = df['PName'].str.startswith('TicketNo-').to_numpy()
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3
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-
is_remove_pcode = df['PCode'] == 10011
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3
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is_remove_pcode = df['PCode'].to_numpy() == 10011
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4
4
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5
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-
drop_index = np.all([is_ticket,
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5
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+
drop_index = np.all([is_ticket, np.concatenate((is_remove_pcode[1:], is_remove_pcode[-1:]))], 0)
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6
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-
res = df.drop([*drop_index, *drop_index+1])
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6
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res = df.drop([*drop_index, *(drop_index+1)])
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7
7
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8
8
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print(res)
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9
9
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# PCode PName Price
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