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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136
5
章
pandas
入門
5.1
pandas
のデータ構造
pandas
を始めるためには、シリーズ（Series）とデータフレーム（DataFrame）という便利なデータ構
造に慣れる必要があります。これらはすべての問題に対する万能な解決策ではないですが、この
2
つの
データ構造によって、ほとんどのアプリケーションにとって信頼できる使いやすい基盤を提供すること
ができます。
5.1.1
シリーズ（
Series
）
シリーズは
1
次元の配列のようなオブジェクトです。シリーズには連続した値（
NumPy
のデータ型と
似たような型を持つ）とそれに関連付けられたインデックスというデータラベルの配列が含まれます。
最もシンプルなシリーズは
1
つのデータ配列で構成されます。
In [11]: obj = pd.Series([4, 7, -5, 3])
In [12]: obj
Out[12]:
0 4
1 7
2 -5
3 3
dtype: i
nt64
コンソールに出力されているシリーズの文字列表現では、インデックスが左側、データ値が右側に
表示されます。ここでは、データに対するインデックスを指定しなかったため、
0
から
N-1
（
N
はデータ
の長さ）のデフォルトのインデックスが作られています。
values
属性と
index
属性を使うと、シリーズ
が持つデータ配列とインデックスオブジェクトをそれぞれ取得することができます。
In [13]: obj.values
Out[13]: array([ 4, 7, -5, 3])
In [14]: obj.index ...
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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.
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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.