回答編集履歴
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Update
test
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@@ -25,3 +25,99 @@
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7,6.00,5.00,5.00
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```
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**追記**
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> 文字列が含まれている場合ではどうしたらいいでしょうか？
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```python
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import numpy as np
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# load
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cols = ('num', 'a', 'b', 'c', 'name')
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tbl = np.loadtxt(
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'data.csv', delimiter=',', skiprows=1,
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dtype={'names': cols,
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'formats': (*(np.int64,)*4, (np.str_, 10))})
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# mean
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names = np.unique(tbl['name']).tolist()
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tbl = np.array([tbl[n] for n in cols])[:-1].T.astype(int)
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result = np.array([tbl[tbl[:,0]==i].mean(axis=0) for i in np.unique(tbl[:,0])])
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# save
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fmt = ['{:.0f}'] + ['{:.2f}']*3
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result = [[fmt[m].format(i) for m, i in enumerate(l)] + [names[n]] for n, l in enumerate(result.tolist())]
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np.savetxt('result.csv', result, delimiter=',', header=','.join(cols), fmt='%s')
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# result.csv
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# num,a,b,c,name
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1,3.00,3.00,6.00,aa
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2,7.00,1.00,2.00,bb
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3,3.33,5.67,6.67,cc
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7,6.00,5.00,5.00,dd
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```
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一方、Pandas を使うと簡単にできます。
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```python
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import pandas as pd
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df = pd.read_csv('data.csv')
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dfx = df.groupby('num').mean().join(df['name'])
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dfx.to_csv('result.csv', float_format='%.2f')
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# result.csv
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num,a,b,c,name
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1,3.00,3.00,6.00,aa
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2,7.00,1.00,2.00,bb
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3,3.33,5.67,6.67,cc
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7,6.00,5.00,5.00,dd
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```
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