October 2017
Intermediate to advanced
480 pages
9h 49m
Japanese
Content preview from Rではじめるデータサイエンス
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148
9
章
tidyr
によるデータ整理
separate(code, c("new", "var", "sexage")) %>%
select(-new, -iso2, -iso3) %>%
separate(sexage, c("sex", "age"), sep = 1)
1. このケーススタディでは、
na.rm = TRUE
として正しい値があるかどうかを確認しやすくした。
これは妥当か。このデータセットで欠損値がどう表されていたか考えよう。これらは暗黙的欠
損値か。
NA
と0との違いは何か。
2.
mutate()
のステップ（
mutate(key = stringr::str_replace(key, "newrel", "new_rel"))
）
を無視すると何が起こるか。
3.
iso2
と
iso3
が
country
と重複していると述べたが、これを確認しなさい。
4. 各国、年、性別について、結核の総症例を計算しなさい。データの情報がよくわかるよう可視
化しなさい。
9.7
非整理データ
次のテーマに移る前に、非整理データについて説明しておきましょう。本章の初めで、否定的な
意味を込めて「滅茶苦茶」という言葉を非整理データを指すのに使いました。これは言い過ぎでしょ
う。非整理データ
にも多くの有用かつ信頼性のあるデータ構造があります。他のデータ構造を使う
主な理由は次の2つです。
●
他の表現に性能上またはスペースに関する大幅な利点がある。
●
整理データの方式とは大きく異なるデータ格納方
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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.