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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2.2
IPython
の基礎
21
図2-3 既存Jupyter Notebook の例
2.2.3
タブ補完
python
コマンドで起動される標準の
Python
インタプリタと比べて、
IPython
シェルは表面上の違い
があるだけのように見えます。しかし大きな改善点として、タブ補完機能が挙げられます。これは多く
の
IDE
や対話的分析環境でも実装されているものです。
IPython
シェルに式の一部を入力してタブキー
を押すと、オブジェクトや関数といった変数のうち、その時点で参照可能な名前空間からマッチする候
補を提示してくれます。
In [1]: an_apple = 27
In [2]: an_example = 42
In [3]: an<Tab>
an_apple and an_example any
この例では、
an
まで入力して補完しています。その結果、事前に定義されていた
2
つの変数
an_
apple
,
an_example
に加え、
Python
キーワードである
and
と組み込み関数の
any
が候補として表示され
ています。また別の例として、あるオブジェクト変数のメソッドやデータ属性を補完することもできま
す。ピリオドまで入力してタブ補完してみましょう。
22
2
章
Python
の基礎、
IPython
と
Jupyter ...
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