Python:用中值替换异常值 [英] Python: replacing outliers values with median values

问题描述

我有一个 python 数据框，其中有一些异常值.如果这些值不存在，我想用数据的中值替换它们.

I have a python data-frame in which there are some outlier values. I would like to replace them with the median values of the data, had those values not been there.

id         Age
10236    766105
11993       288
9337        205
38189        88
35555        82
39443        75
10762        74
33847        72
21194        70
39450        70

所以，我想用剩余数据集的数据集的中值，即70,70,72,74,75的中值替换所有>75的值.

So, I want to replace all the values > 75 with the median value of the dataset of the remaining dataset, i.e., the median value of 70,70,72,74,75.

我正在尝试执行以下操作:

I'm trying to do the following:

1. 用0代替，所有大于75的值
2. 用中值替换 0.

但不知何故，下面的代码不起作用

But somehow, the below code not working

df['age'].replace(df.age>75,0,inplace=True)

推荐答案

我想这就是你要找的，你可以用 loc 来赋值.然后就可以填nan

I think this is what you are looking for, you can use loc to assign value . Then you can fill the nan

median = df.loc[df['Age']<75, 'Age'].median()
df.loc[df.Age > 75, 'Age'] = np.nan
df.fillna(median,inplace=True)

你也可以在一行中使用 np.where

You can also use np.where in one line

df["Age"] = np.where(df["Age"] >75, median,df['Age'])

您也可以使用 .mask 即

You can also use .mask i.e

df["Age"] = df["Age"].mask(df["Age"] >75, median)

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