pandas for循环删除列并插补高于和低于20%的值[已关闭]

8iwquhpp 于 2022-12-21 发布在其他

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如何创建一个for循环来删除包含20%以上空值的列，并在Pandas数据框中用平均值插补其余列，而所有要素都包含浮点数和Nan（绝对空值）空值
我无法创建一个具有如此多功能性的for循环，

pandas

来源：https://stackoverflow.com/questions/74853562/for-loop-to-drop-columns-and-impute-values-above-and-below-20

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按热度按时间

mspsb9vt1#

您可以使用：

# identify the columns with > 20% NaN
m = df.isna().mean().gt(0.2)

# replace the NaN by the mean
df.loc[:, m] = df.loc[:, m].fillna(df.loc[:, m].mean())

输入示例：

np.random.seed(0)
df = pd.DataFrame(np.random.choice([0, 1, 2, 3, np.nan], size=(10, 10)))

     0    1    2    3    4    5    6    7    8    9
0  NaN  0.0  3.0  3.0  3.0  1.0  3.0  2.0  NaN  0.0
1  0.0  NaN  2.0  1.0  0.0  1.0  1.0  0.0  1.0  NaN
2  3.0  0.0  3.0  0.0  2.0  3.0  0.0  1.0  3.0  3.0
3  3.0  0.0  1.0  1.0  1.0  0.0  2.0  NaN  3.0  3.0
4  2.0  NaN  2.0  0.0  0.0  NaN  0.0  NaN  1.0  NaN
5  1.0  2.0  2.0  0.0  1.0  1.0  1.0  1.0  3.0  3.0
6  2.0  3.0  0.0  3.0  NaN  1.0  2.0  NaN  3.0  NaN
7  NaN  NaN  3.0  NaN  NaN  NaN  0.0  NaN  3.0  2.0
8  0.0  1.0  1.0  3.0  0.0  0.0  1.0  2.0  NaN  2.0
9  0.0  3.0  2.0  2.0  0.0  1.0  0.0  2.0  2.0  3.0

输出：

0         1    2    3    4    5    6         7    8         9
0  NaN  0.000000  3.0  3.0  3.0  1.0  3.0  2.000000  NaN  0.000000
1  0.0  1.285714  2.0  1.0  0.0  1.0  1.0  0.000000  1.0  2.285714
2  3.0  0.000000  3.0  0.0  2.0  3.0  0.0  1.000000  3.0  3.000000
3  3.0  0.000000  1.0  1.0  1.0  0.0  2.0  1.333333  3.0  3.000000
4  2.0  1.285714  2.0  0.0  0.0  NaN  0.0  1.333333  1.0  2.285714
5  1.0  2.000000  2.0  0.0  1.0  1.0  1.0  1.000000  3.0  3.000000
6  2.0  3.000000  0.0  3.0  NaN  1.0  2.0  1.333333  3.0  2.285714
7  NaN  1.285714  3.0  NaN  NaN  NaN  0.0  1.333333  3.0  2.000000
8  0.0  1.000000  1.0  3.0  0.0  0.0  1.0  2.000000  NaN  2.000000
9  0.0  3.000000  2.0  2.0  0.0  1.0  0.0  2.000000  2.0  3.000000

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pandas for循环删除列并插补高于和低于20%的值[已关闭]

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