用数据框中组的平均值替换列值 [英] Replace a column values with its mean of groups in dataframe

问题描述

我有一个 DataFrame

I have a DataFrame as

Page    Line    y
1        2      3.2
1        2      6.1
1        3      7.1
2        4      8.5
2        4      9.1

我必须将 y 列替换为其分组平均值的值.我可以使用此代码使用一列进行分组.

I have to replace column y with values of its mean in groups. I can do that grouping using one column using this code.

df['y'] = df['y'].groupby(df['Page'], group_keys=False).transform('mean') 

我正在尝试通过页面"和行"的组来替换 y 的值.像这样，

Page    Line    y
1        2      4.65
1        2      4.65
1        3      7.1
2        4      8.8
2        4      8.8

我在这个网站上搜索了很多答案，但找不到这个应用程序.将 python3 与 Pandas 结合使用.

I have searched through a lot of answers on this site but couldn't find this application. Using python3 with pandas.

推荐答案

您需要列名列表，groupby 参数by:

by :映射、函数、标签或标签列表

by : mapping, function, label, or list of labels

用于确定 groupby 的组.如果 by 是一个函数，它会在对象索引的每个值上调用.如果传递了 dict 或 Series，则 Series 或 dict VALUES 将用于确定组(首先对齐 Series 的值；请参阅 .align() 方法).如果传递了 ndarray，则按原样使用这些值来确定组.标签或标签列表可以通过 self 中的列传递给 group.请注意，元组被解释为(单个)键.

Used to determine the groups for the groupby. If by is a function, it’s called on each value of the object’s index. If a dict or Series is passed, the Series or dict VALUES will be used to determine the groups (the Series’ values are first aligned; see .align() method). If an ndarray is passed, the values are used as-is determine the groups. A label or list of labels may be passed to group by the columns in self. Notice that a tuple is interpreted a (single) key.

df['y'] = df.groupby(['Page', 'Line'])['y'].transform('mean') 
print (df)
   Page  Line     y
0     1     2  4.65
1     1     2  4.65
2     1     3  7.10
3     2     4  8.80
4     2     4  8.80

您的解决方案应更改为此语法糖 - 通过列表中的系列:

Your solution should be changed to this syntactic sugar - pass Series in list:

df['y'] = df['y'].groupby([df['Page'], df['Line']]).transform('mean') 

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