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
339
5H 5
KC 10
2C 2
dtype: int64
2
つのランダムなカードをそれぞれのスート
＊
1
から取り出したい場合、カード名の最後の文字がスー
トを表しているので、これを利用してグループ化し、
apply
を使います。
In [111]: get_suit = lambda card: card[-1] #
最後の文字がスートを表す
In [112]: deck.groupby(get_suit).apply(draw, n=2)
Out[112]:
C 2C 2
3C 3
D KD 10
8D 8
H KH 10
3H 3
S 2S 2
4S 4
dtype: int64
別の方法として、次のようにも書けます。
In [113]: deck.groupby(get_suit, group_keys=False).apply(draw, n=2)
Out[113]:
KC 10
JC 10
AD 1
5D 5
5H 5
6H 6
7S 7
KS 10
dtype: int64
10.3.5
例：グループの加重平均と相関
groupby
の分離−適用−結合パラダイムのもとでは、グループの加重平均値のような、データフレー
ムの複数の列間の操作や
2
つのシリーズの操作も可能です。グループキー、値、何らかの重み（
weights
）
を含む次のようなデータセットを例に見てみましょう。
In [114]: df = pd.DataFrame({'category': ['a', 'a', ...
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