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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316
10
章 データの集約とグループ演算
10.1
GroupBy
の仕組み
R
言語で多くの有名なパッケージを作っている
Hadley Wickham
によって、グループ演算のプロセス
を説明するために作られた言葉が分離−適用−結合（
split-apply-combine
）です。プロセスの最初の段
階では、
pandas
のオブジェクト（シリーズやデータフレームなど）に格納されているデータが、指定し
た
1
つ以上のキーによって分離されます。分離はオブジェクトの特定の軸を使って行われます。例えば、
データフレームはその行（
axis=0
）でも列（
axis=1
）でもグループ処理をすることができます。分離が終
わったら、それぞれのグループに関数が適用され、新しい値が生成されます。最後に、これらの関数
を適用した結果が結合されて結果を戻すオブジェクトに格納されます。戻るオブジェクトの形式は、大
抵はデータに行った処理の内容に依存します。図10-1はシンプルなグループ集
約操作のモデルです。
結合適用分離
データキー
図10-1 グループ集約操作の図解
グループ化に使用するキーはさまざまな形式を取ることができ、また、すべて同じ型である必要もあ
りません。
●
値のリストや配列（グループされる軸と同じ長さのもの）。
●
データフレームの列名を示す値。
●
ディクショナリ形式あるいはシリーズ形式（グループされる軸の値とグループ名の間の対応を取
れるもの）。
●
軸のインデックス、あるいは、各インデックスのラベルに対して呼び出される関数。
10.1 ...
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