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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135
5
章
pandas
入門
この本の残りの部分では
pandas
に注目していき、
pandas
を主要なツールとして扱います。
pandas
は高度なデータ構造を持ち、また、
Python
でデータの整理や分析を素早く簡単に行うために設計され
た分析ツールも持っています。
pandas
は、
SciPy
や
NumPy
などの数値計算ツールや、
statsmodels
や
scikit-learn
などの分析用ライブラリ、また、
Matplotlib
などの可視化ライブラリと連携して使われるこ
とが多いです。
pandas
は、
NumPy
のような配列ベースの計算スタイルや配列ベースの関数を採用して
います。また、
NumPy
と同様に
for
ループを使わないデータ処理を好みます。
pandas
は、多くのコーディング用法を
NumPy
から採用していますが、その中で最も大きな違いは、
pandas
はテーブル形式のデータや不均一なデータを扱うために設計されて
いるというところにありま
す。
NumPy
は、均一な数値データの扱いに最も適しています。
2010
年にオープンソースプロジェクトになって以来、
pandas
は非常に大きなライブラリに成長し、
現実世界の広範なユースケースに適用できるものになりました。開発者コミュニティも成長して
800
人
以上の貢献者がいます。彼らは、日々のデータ問題を解決するために
pandas
を使いながら、プロジェ
クトの構築を手伝ってくれています。
この本の残りの部分では、以下のような
pandas
のインポート文を習慣として使うことに
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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.