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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264
8
章 データラングリング：連結、結合、変形
最後に取り上げるのは、データフレームの行のインデックスに、特に重要な情報が含まれていない
場合の処理です。
In [103]: df1 = pd.DataFrame(np.random.randn(3, 4), columns=['a', 'b', 'c', 'd'])
In [104]: df2 = pd.DataFrame(np.random.randn(2, 3), columns=['b', 'd', 'a'])
In [105]: df1
Out[105]:
a b c d
0 1.246435 1.007189 -1.296221 0.274992
1 0.228913 1.352917 0.886429 -2.001637
2 -0.371843 1.669025 -0.438570 -0.539741
In [1
06]: df2
Out[106]:
b d a
0 0.476985 3.248944 -1.021228
1 -0.577087 0.124121 0.302614
この場合には、
ignore_index=True
と指定すればインデックスが振り直されます。
In [107]: pd.concat([df1, df2], ignore_index=True)
Out[107]:
a b c d
0 1.246435 1.007189 -1.296221 0.274992
1 0.228913 1.352917 0.886429 -2
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