November 2017
Intermediate to advanced
328 pages
6h 51m
Japanese
Content preview from 入門 PySpark ―PythonとJupyterで活用するSpark 2エコシステム
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56
4
章 データのモデリングの準備
4.1
重複、計測値の欠落、外れ値のチェック
データを完全にテストして、それに時間をかけても大丈夫なことが確実になるまでは、データを信用
したり使ったりするべきではありません。このセクションでは、重複や計測値の欠落、そして外れ値の
扱い方を紹介します。
4.1.1
重複
重複は、データセット中では複数の行に現れながら、よく調べてみれば同じに見えるようなデータで
す。すなわち、それら 2つ（以上）の行を並べて比較してみれば、すべての部分がまったく同じ値を持っ
ているということです。
一方で、データに何らかの IDが与えられており、レコードを区別できるようになっている（あるいは
たとえば、レコードが特定のユーザーに紐付けられている）ような場合には、一見したところでは重複
に見えたものが、実はそうではないかもしれません。場合によってはシステムの障害で間違った IDが生
成されることもあります。そういった場合には、同じ ID が本当に重複なのかを調べたり、あるいは新し
いIDの仕組みを考えたりしなければならないかもしれません。
下記の例を考えてみましょう。
df = spark.createDataFrame([
(1, 144.5, 5.9, 33, 'M'),
(2, 167.2, 5.4, 45, 'M'),
(3, 124.1, 5.2, 23, 'F'),
(4, 144.5, 5.9, 33, 'M'),
(5, 133.2, 5.7, 54, 'F'),
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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.