August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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12
1 章 探索的データ解析
14 3
15 1
51 1
6, 7, 8
ポンドでの結果は合っていますし、
0
〜
5
と
9
〜
95
の個数をそれぞれ足し
合わせると、それらもあっています。しかし、細かく見れば、データのエラーがわか
ります。
51
ポンドの新生児はありえません。
このエラーを処理するため、
CleanFemPreg
に次の一行を追加しました。
df.birthwgt_lb[df.birthwgt_lb > 20] = np.nan
この命令は、不正値を
np.nan
で置き換えます。角括弧の式は、論理型の
Series
で、
True
は条件が満たされていることを示します。論理型の
Series
をインデックスに使
うと、その条件を満たす要素だけが選ばれます。
1.8
解釈
データを効率的に処理するためには、統計のレベルと文脈のレベルという
2
つのレ
ベルを同時に考える必要があります。
例えば、何人かの回答者の妊娠結果を見てみましょう。データファイルの構成が妊
娠単位のため、回答者ごとの妊娠データを集めるには処理が必要です。それを行う関
数は次のようになります。
def MakePregMap(df):
d = defaultdict(list)
for index, caseid in df.caseid.iteritems():
d[caseid].append(index)
return d
df
は妊娠データの
DataFrame
です。メソッド
iteritems
が各妊娠のインデックス
（行番号）と
caseid
とを順に処理します。 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.