pandas:当索引不唯一时使用 diff 和 groupby 的问题 [英] pandas: problem using diff with groupby when index is non-unique

问题描述

我正在使用 pandas(版本 0.20.3) 我想将 diff() 方法与 groupby() 一起应用，但不是 DataFrame，结果是下划线".

I am using pandas (version 0.20.3) and I want to apply the diff() method with groupby() but instead of a DataFrame, the result is an "underscore".

代码如下:

import numpy as np
import pandas as pd

# creating the DataFrame
data = np.random.random(18).reshape(6,3)
indexes = ['B']*3 + ['A']*3
columns = ['x', 'y', 'z']
df = pd.DataFrame(data, index=indexes, columns=columns)
df.index.name = 'chain_id'

# Now I want to apply the diff method in function of the chain_id
df.groupby('chain_id').diff()

结果是一个下划线！

注意 df.loc['A'].diff() 和 df.loc['B'].diff() 确实返回了预期的结果，所以我不明白为什么它不能与 groupby() 一起使用.

Note that df.loc['A'].diff() and df.loc['B'].diff() do return the expected results so I don't understand why it wouldn't work with groupby().

推荐答案

IIUC,您的错误:无法从重复轴重新索引

df.reset_index().groupby('chain_id').diff().set_index(df.index)
Out[859]: 
                 x         y         z
chain_id                              
B              NaN       NaN       NaN
B        -0.468771  0.192558 -0.443570
B         0.323697  0.288441  0.441060
A              NaN       NaN       NaN
A        -0.198785  0.056766  0.081513
A         0.138780  0.563841  0.635097

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