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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334
10
章 データの集約とグループ演算
Out[81]:
total_bill tip smoker day time size tip_pct
88 24.71 5.85 No Thur Lunch 2 0.236746
185 20.69 5.00 No Sun Dinner 5 0.241663
51 10.29 2.60 No Sun Dinner 2 0.252672
149 7.51 2.00 No Thur Lunch 2 0.266312
232 11.61 3.39 No Sat Dinner 2 0.291990
109 14.31 4.00 Yes Sat Dinner
2 0.279525
183 23.17 6.50 Yes Sun Dinner 4 0.280535
67 3.07 1.00 Yes Sat Dinner 1 0.325733
178 9.60 4.00 Yes Sun Dinner 2 0.416667
172 7.25 5.15 Yes Sun Dinner 2 0.710345
10.3.2
分位点とビン分析
「8章 データラングリング：連結、結合、変形」で触れた通り、
pandas
はいくつかのツールを持っ
ています。例として、
cut
や
qcut
が挙げられます。
cut
はデータを同じ長さのビンに分割して入れる動
作をし、
qcut
はサンプルデータの分位点でデータを分割します。これらの関数を
groupby
と組み合わせ
て使うとデータセットのビン分析や分位点分析
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