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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6.1
テキスト形式のデータの読み書き
191
2000-01-02,1
2000-01-03,2
2000-01-04,3
2000-01-05,4
2000-01-06,5
2000-01-07,6
6.1.3
区切り文字で区切られた形式を操作する
テーブル形式のデータの大半は、
pandas.read_table
のような関数を用いてディスクから読み込めま
す。しかし場合によっては、手での処理が多少必要になるかもしれません。
read_table
では取り扱え
ないような、一部の行の形式が異なるファイルを受け取ることは、珍しくありません。ここでは基本的
なツールを説明するために、次のような小さな
CSV
ファイルを考えてみましょう。
In [54]: !cat examples/ex7.csv
"a","b","c"
"1","2","3"
"1","2","3"
区切り文字が
1
文字のどんなファイルに対しても、
Python
組み込みの
csv
モジュールを使えます。こ
のモジュールを使うには、ファイルやファイル系のオブジェクトをオープンして
csv.reader
に渡してく
ださい。
import csv
f = open('examples/ex7.csv')
reader = csv.reader(f)
csv.reader
から戻された
reader
に対して、ファイルの各行を扱うように繰り返し処理を行うと、引
用符がすべて取り除かれて、各行の値のタプルが戻されます。
In [56]: for line in reader:
....: print(line) ...
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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.