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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5.1
pandas
のデータ構造
147
型 説明
ディクショナリをバリューに持つ
ディクショナリ
バリューになっている各ディクショナリが列になる。シリーズをバリューに持
つディクショナリと同様に、ディクショナリのキーは統合されて、行インデッ
クスになる。
ディクショナリ、または、シリー
ズのリスト
各要素はデータフレームの行になる。ディクショナリのキーや、シリーズの
インデックスはデータフレームの列ラベルになる。
リスト、または、タプルのリスト
2
次元
ndarray
と同様に扱われる。
別のデータフレーム 何も指定されなければ、入力に使用したデータフレームのインデックスがイ
ンデックスとして使用される。
NumPy
の
MaskedArray
マスクされた値がデータフレームでは欠損値になるという点を除いて、
2
次元
ndarray
の場合と同様に扱われる。
5.1.3
インデックスオブジェクト
pandas
のインデックスオブジェクトは、軸のラベルやその他のメタデータ（軸の
name
属性や
names
属
性など）を保持する役目を持っています。シリーズやデータフレームを初期化するときに、配列やシー
ケンスなどで指定したラベルは、内部的にはインデックスオブジェクトに変換されます。
In [76]: obj = pd.Series(range(3), index=['a', 'b', 'c'])
In [77]: index = obj.index
In [78]: index
Out[78]: Index(['a', 'b', 'c'], dtype='object') ...
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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.
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.