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
189
処理を行い、
'key'
列に含まれる値ごとに個数を集計できます。
chunker = pd.read_csv('examples/ex6.csv', chunksize=1000)
tot = pd.Series([])
for piece in chunker:
tot = tot.add(piece['key'].value_counts(), fill_value=0)
tot = tot.sort_values(ascending=False)
次のような結果が得られます。
In [40]: tot[:10]
Out[40]:
E 368.0
X 364.0
L 346.0
O 343.0
Q 340.0
M 338.0
J 337.0
F 335.0
K 334.0
H 330.0
dtype: float64
TextFileReader
は
get_chunk
メソッドも持っています。このメソッドを使うと任意のサイズずつ読み
込めます
＊
1
。
6.1.2
テキスト形式でのデータの書き出し
データは、区切り文字で区切られた形式でのエクスポートもできます。先ほど読み取った
CSV
ファ
イルの
1
つを例に取って考えてみましょう。
In [41]: data = pd.read_csv('examples/ex5.csv')
In [42]: data
Out[42]:
something a b c d message
0 one 1 2 3.0 4 NaN
1 two 5 6 NaN 8 world ...
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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.