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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356
11
章 時系列データ
2011-01-02 -0.204708
2011-01-05 0.478943
2011-01-07 -0.519439
2011-01-08 -0.555730
dtype: float64
ここまでのすべてのものはデータフレームでも同様に存在し、行をインデックス参照できます。
In [60]: dates = pd.date_range('1/1/2000', periods=100, freq='W-WED')
In [61]: long_df = pd.DataFrame(np.random.randn(100, 4),
....: index=dates,
....: columns=['Colorado', 'Texas',
....:
'New York', 'Ohio'])
In [62]: long_df.loc['5-2001']
Out[62]:
Colorado Texas New York Ohio
2001-05-02 -0.006045 0.490094 -0.277186 -0.707213
2001-05-09 -0.560107 2.735527 0.927335 1.513906
2001-05-16 0.538600 1.273768 0.667876 -0.969206
2001-05-23 1.676091 -0.817649 0.050188 1.951312
2001-05-30 3.260383 0.963301 1.201206 ...
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