pandas 为通过 groupby 应用结果设置列名
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Set column name for apply result over groupby
提问by MrT
This is a fairly trivial problem, but its triggering my OCD and I haven't been able to find a suitable solution for the past half hour.
这是一个相当微不足道的问题，但它触发了我的强迫症，在过去的半小时里我一直找不到合适的解决方案。
For background, I'm looking to calculate a value (let's call it F) for each group in a DataFrame derived from differentaggregated measures of columns in the existing DataFrame.
作为背景，我希望为 DataFrame 中的每个组计算一个值（我们称之为 F），这些值源自现有 DataFrame 中列的不同聚合度量。
Here's a toy example of what I'm trying to do:
这是我正在尝试做的一个玩具示例：
import pandas as pd
import numpy as np
df = pd.DataFrame({'A': ['X', 'Y', 'X', 'Y', 'Y', 'Y', 'Y', 'X', 'Y', 'X'],
'B': ['N', 'N', 'N', 'M', 'N', 'M', 'M', 'N', 'M', 'N'],
'C': [69, 83, 28, 25, 11, 31, 14, 37, 14, 0],
'D': [ 0.3, 0.1, 0.1, 0.8, 0.8, 0. , 0.8, 0.8, 0.1, 0.8],
'E': [11, 11, 12, 11, 11, 12, 12, 11, 12, 12]
})
df_grp = df.groupby(['A','B'])
df_grp.apply(lambda x: x['C'].sum() * x['D'].mean() / x['E'].max())
What I'd like to do is assign a name to the result of apply(or lambda). Is there anyway to do this without moving lambdato a named function or renaming the column after running the last line?
我想做的是为apply(or lambda)的结果指定一个名称。无论如何，lambda在运行最后一行后，是否可以在不移动到命名函数或重命名列的情况下执行此操作？
回答by Alexander
Have the lambda function return a new Series:
让 lambda 函数返回一个新系列：
df_grp.apply(lambda x: pd.Series({'new_name':
x['C'].sum() * x['D'].mean() / x['E'].max()}))
# or df_grp.apply(lambda x: x['C'].sum() * x['D'].mean() / x['E'].max()).to_frame('new_name')
new_name
A B
X N 5.583333
Y M 2.975000
N 3.845455
回答by Zero
You could convert your seriesto a dataframeusing reset_index()and provide name='yout_col_name'-- The name of the column corresponding to the Series values
您可以将您的转换series为dataframeusingreset_index()并提供name='yout_col_name'-- 与系列值对应的列的名称
(df_grp.apply(lambda x: x['C'].sum() * x['D'].mean() / x['E'].max())
.reset_index(name='your_col_name'))
A B your_col_name
0 X N 5.583333
1 Y M 2.975000
2 Y N 3.845455
