August 2017
Intermediate to advanced
500 pages
12h 3m
Japanese
Content preview from PythonとJavaScriptではじめるデータビジュアライゼーション
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179
8.4 DataFrame
象とする異種情報が含まれています。一般に
NumPy
配列は同種の数値の高速処理に使いますが、
pandas
はカテゴリデータ、時系列、実世界のデータの異種性を反映した項目を扱うように設計さ
れています。そのため、
pandas
はデータ可視化に有効です。
pandas
が処理の対象とするデータの種類がわかったので、
pandas
が使うデータ構造を調べてみ
ましょう。
8.4
DataFrame
通常、
pandas
セッションの第
1
段階は
DataFrame
にデータを読み込むことです。そのためのさ
まざまな方法は後の節で説明します。まず、ファイルから
JSON
データ
nobel_winners.json
を読
み込みましょう。
read_json
は、指定した
JSON
ファイルからパースした
DataFrame
を返します。
慣例により、
DataFrame
変数は
df
から始めます。
import pandas as pd
df = pd.read_json('data/nobel_winners.json')
次に、
DataFrame
が入手できたので、その内容を調べてみます。
DataFrame
の行
/
列形式の構造
は、
head
メソッドを使って（デフォルトで）最初の
5
つの項目を表示すると簡単にわかります。
図
8-1
に、
DataFrame
の主要要素をハイライトした
IPython
（または
Jupyter
（
http://jupyter.
org/
））
Notebook
の出力を表します。■
8.4.1
インデックス
DataFrame ...
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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.