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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4.8
まとめ
133
In [264]: walks.max()
Out[264]: 138
In [265]: walks.min()
Out[265]: -133
さらにこの
5,000
回のランダムウォークから、今回は距離
30
（＋
30
あるいは−
30
）への初到達時間を求
めてみましょう。これには少し考慮が必要で、
5,000
回の試行のすべてが必ず距離
30
に到達しているわ
けではありません。
この確認には、前出の真偽値配列関数
any
を使います。
In [266]: hits30 = (np.abs(walks) >= 30).any(1)
In [267]: hits30
Out[267]: array([False, True, False, ..., False, True, False], dtype=bool)
In [268]: hits30.sum() # 30
もしくは
-30
に到達した数
Out[268]: 3410
このようにして得られた真偽値配列
hits30
を用いて
5,000
件の中から距離
30
に到達できた試行を選
び出します。そのそれぞれの抽出結果に対して
argmax
を適用し、一番最初に距離
30
に到達したイン
デックスを得ます。
In [269]: crossing_times = (np.abs(walks[hits30]) >= 30).argmax(1)
In [270]: crossing_times.mean()
Out[270]: 498.88973607038122
このランダムウォーク
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