July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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10.3
apply
メソッド：一般的な分離−適用−結合の方法
331
もちろん、インデックス付けされた結果に対して
reset_index
メソッドを呼ぶことで、いつでもこの
形式にすることは可能です。しかし、
as_index=False
を使った場合は、不必要な計算が回避されてい
ます。
10.3
apply
メソッド：一般的な分離
−
適用
−
結合の方法
最も一般的な目的を持つ
GroupBy
のメソッドは
apply
で、この節の残りの部分の主なテーマです。
図10-2にあるように、
apply
はオブジェクトを操作するためのピースに分離し、それぞれのピースに対
して渡された関数を適用し、その後それらのピースを結合します。
結合適用分離
データキー
図10-2 グループ集約操作の図解
先ほどのチップのデータセットに話を戻して、
tip_pct
値のグループ別上位
5
件を選択したい場合を
考えます。まずは、特定の列の上位の値を持つ行を選択する関数を書きます。
In [74]: def top(df, n=5, column='tip_pct'):
....: return df.sort_values(by=column)[-n:]
In [75]: top(tips, n=6)
Out[75]:
total_bill tip smoker day time size tip_pct
109 14.31 4.00 Yes Sat Dinner 2 0.279525
183 23.17 6.50 Yes Sun Dinner 4 0
.280535 ...
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