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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444
14
章 データ分析の実例
ここではユーザ合計数が小さいものから順に
agg_counts
を並べ替えようとしています。並べ
替えたデータを得るために
indexer
を生成しました。
indexer
の
2
列目を用い、次のようにデー
タ元の
agg_counts
の要素を
indexer
の順に取ってくればよい、ということです。
agg_counts.take([24]) -> America/Mazatlan 1 0
agg_counts.take([20]) -> America/La_Paz 0 1
agg_counts.take([21]) -> America/Lima 0 1
agg_counts.take([92]) -> Europe/Volgograd 0 1
agg_counts.take([87]) -> Eur
ope/Sofia 0 1
この考え方について説明します。
aggsort()
で得られた
indexer
というシリーズのインデック
スには意味がありません。
indexer
は
agg_counts
を基に生成されており、
agg_counts
の
1
列目
と
indexer
の
1
列目はまったく同一の並び順で構成されています。
indexer
の
1
列目のタイム
ゾーンが示すのは、そのタイムゾーンが
agg_counts
では何行目のレコードだったのか、とい
うだけです。したがって、
indexer
の先頭
5
件は次のように読み解くことができます。
ソート結果
1
番目
agg_counts
のインデックス
24
の要素
(23
番目
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