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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7.2
データの変形
215
In [42]: df.fillna(method='ffill', limit=2)
Out[42]:
0 1 2
0 0.476985 3.248944 -1.021228
1 -0.577087 0.124121 0.302614
2 0.523772 0.124121 1.343810
3 -0.713544 0.124121 -2.370232
4 -1.860761 NaN -2.370232
5 -1.265934 NaN -2.370232
少し工夫すると、
fillna
を用いて、他にもさまざまな埋め方ができます。例えば、シリーズの平均
値や中央値で穴を埋めてもよいでしょう。
In [43]: data = pd.Series([1., NA, 3.5, NA, 7])
In [44]:
data.fillna(data.mean())
Out[44]:
0 1.000000
1 3.833333
2 3.500000
3 3.833333
4 7.000000
dtype: float64
fillna
に関しては、表7-2のリファレンスも参照してください。
表7-2 メソッドの引数
引数 説明
value
欠損値の穴埋めに用いられるスカラー値、またはディクショナリ系のオブジェクト。
method
穴埋め方法を指定する。他の引数が何も指定されなかった場合、デフォルトでは
'ffill'
が
適用される。
axis
穴埋めをしたい軸。デフォルトでは
axis=0
（行方向）。
inplace
コピーを作
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