pandas 中的多维/嵌套数据帧/数据集/面板 [英] Multi-dimensional/Nested DataFrame/Dataset/Panel in Pandas

问题描述

我想将一些多维数据存储在大熊猫数据框或面板中，以便我能够返回，例如：

I would like to store some multidimensional data in a pandas dataframe or panel such that I would like to be able to return for example:

1. A跑步者A的所有时间，比赛A


2. 某一年的A组的所有时间（和名称）都说2015年

示例数据将如下所示，请注意，并不是所有赛跑者都将拥有所有年份或所有种族的数据。

Example data would look something like this, note that not all runners will have data for all years or all races.

可以任何人都建议使用熊猫或其他任何方式做一个好办法？

Could anyone suggest a good way to do this with Pandas or any other way?

Name     | Gender | Age
Runner A | Male   | 35
    Race A
        Year | Time     
        2015 | 2:35:09  
        2014 | 2:47:34
        2013 | 2:50:12
    Race B
        Year | Time
        2013 | 1:32:07

Runner B | Male | 29
    Race A
        Year | Time
        2015 | 3:05:56

Runner C | Female | 32
    Race B
        Year | Time
        1998 | 1:29:43

推荐答案

我想你可以使用 Multiindex ，然后通过切片机：

I think you can use Multiindex and then select data by slicers:

import pandas as pd

df = pd.DataFrame({'Time': {('Runner A', 'Male', 35, 'Race A', 2014): '2:47:34', ('Runner C', 'Female', 32, 'Race B', 1998): '1:29:43', ('Runner B', 'Male', 29, 'Race A', 2015): '3:05:56', ('Runner A', 'Male', 35, 'Race A', 2013): '2:50:12', ('Runner A', 'Male', 35, 'Race B', 2013): '1:32:07', ('Runner A', 'Male', 35, 'Race A', 2015): '2:35:09'}})
print (df)
                                   Time
Runner A Male   35 Race A 2013  2:50:12
                          2014  2:47:34
                          2015  2:35:09
                   Race B 2013  1:32:07
Runner B Male   29 Race A 2015  3:05:56
Runner C Female 32 Race B 1998  1:29:43

#index has to be fully lexsorted
df.sort_index(inplace=True)
print (df)
                                   Time
Runner A Male   35 Race A 2013  2:50:12
                          2014  2:47:34
                          2015  2:35:09
                   Race B 2013  1:32:07
Runner B Male   29 Race A 2015  3:05:56
Runner C Female 32 Race B 1998  1:29:43

idx = pd.IndexSlice
print (df.loc[idx['Runner A',:,:,'Race A',:],:])
                                 Time
Runner A Male 35 Race A 2013  2:50:12
                        2014  2:47:34
                        2015  2:35:09

print (df.loc[idx[:,:,:,'Race A',2015],:])
                                 Time
Runner A Male 35 Race A 2015  2:35:09
Runner B Male 29 Race A 2015  3:05:56

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