回答編集履歴
2
Update
test
CHANGED
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@@ -9,8 +9,8 @@
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9
9
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dfx = (
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10
10
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df1.groupby('col1', as_index=False)
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11
11
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.apply(lambda x: pd.Series(
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12
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-
x
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12
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+
x.iloc[:,1:].unstack()
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13
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-
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13
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+
.values[~np.in1d(np.arange(x.shape[0]*(x.shape[1]-1)), [x.shape[0]*2])],
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14
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index=[f'col{i}' for i in range(2,(x.shape[0]*x.shape[1]-1))])))
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15
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print(dfx)
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1
Update
test
CHANGED
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@@ -6,12 +6,11 @@
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6
6
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df1=pd.DataFrame({'col1': ['a', 'a','b','b'],'col2': range(4),'col3':['apple','5','bag','7'],'col4':['apple','sort','bag','table']})
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7
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#df2=pd.DataFrame({'col1': ['a','b'],'col2': ['0','2'],'col3':['1','3'],'col4':['apple','bag'],'col5':['5','7'],'col6':['sort','table']})
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8
8
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9
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-
exclude = [4]
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10
9
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dfx = (
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11
10
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df1.groupby('col1', as_index=False)
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12
11
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.apply(lambda x: pd.Series(
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13
12
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x[x.columns[1:]].unstack()
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14
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-
.values[~np.in1d(np.arange(x.shape[0]*(x.shape[1]-1)),
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13
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+
.values[~np.in1d(np.arange(x.shape[0]*(x.shape[1]-1)), [x.shape[0]*2])],
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index=[f'col{i}' for i in range(2,(x.shape[0]*x.shape[1]-1))])))
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16
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print(dfx)
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