pandas :获取组最小值和相应的索引值

本文介绍了 pandas :获取组最小值和相应的索引值的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

作为一个简单的示例，请考虑以下熊猫数据框:

As a simple example, consider the following pandas dataframe:

import pandas as pd headers = ["city", "year", "births", "deaths", "immigrations", "emigrations"] data = [ ["Gotham", 2016, 1616, 1020, 1541, 1893], ["Gotham", 2015, 1785, 1708, 1604, 1776], ["Gotham", 2014, 1279, 1946, 1991, 1169], ["Gotham", 2013, 1442, 1932, 1960, 1580], ["Metropolis", 2016, 6405, 6393, 5390, 6797], ["Metropolis", 2015, 6017, 5492, 5647, 6994], ["Metropolis", 2014, 6644, 6893, 6759, 5149], ["Metropolis", 2013, 6902, 6160, 5294, 5112], ["Smallville", 2016, 43, 10, 29, 48], ["Smallville", 2015, 16, 21, 17, 19], ["Smallville", 2014, 20, 31, 28, 43], ["Smallville", 2013, 46, 11, 25, 25], ] df = pd.DataFrame(data, columns=headers) df.set_index(["city", "year"], inplace=True)

在控制台输出中如下所示:

which looks like this in console output:

births deaths immigrations emigrations city year Gotham 2016 1616 1020 1541 1893 2015 1785 1708 1604 1776 2014 1279 1946 1991 1169 2013 1442 1932 1960 1580 Metropolis 2016 6405 6393 5390 6797 2015 6017 5492 5647 6994 2014 6644 6893 6759 5149 2013 6902 6160 5294 5112 Smallville 2016 43 10 29 48 2015 16 21 17 19 2014 20 31 28 43 2013 46 11 25 25

问题

对于每个数据列，我想知道每个城市的最低限额以及发生的年份.基本上，我正在尝试获取如下所示的结果数据框:

Problem

For each data column I'd like to know the per-city minimum, together with the year in which it occurred. Basically, I'm trying to obtain a result dataframe that looks like this:

births deaths immigrations emigrations min year min year min year min year city Gotham 1279 2014 1020 2016 1541 2016 1169 2014 Metropolis 6017 2015 5492 2015 5294 2013 5112 2013 Smallville 16 2015 10 2016 17 2015 19 2015

到目前为止已尝试

我能够获得每个城市的最小值，如下所示:

Tried thus far

I was able to get the per-city minimum values as follows:

df.groupby(level="city").min()

但是在那之后我被卡住了.我还没有找到一种方法来获取与最小值对应的年份.这里有人有解决这个问题的好主意吗?

However after that I'm stuck. I haven't been able to find a way to also get the years corresponding to the minimum values. Does anyone here have a good idea for solving this?

推荐答案

In [180]: df.reset_index(level=0).groupby('city').agg(['min','idxmin','max','idxmax']) Out[180]: births deaths immigrations \ min idxmin max idxmax min idxmin max idxmax min city Gotham 1279 2014 1785 2015 1020 2016 1946 2014 1541 Metropolis 6017 2015 6902 2013 5492 2015 6893 2014 5294 Smallville 16 2015 46 2013 10 2016 31 2014 17 emigrations idxmin max idxmax min idxmin max idxmax city Gotham 2016 1991 2014 1169 2014 1893 2016 Metropolis 2013 6759 2014 5112 2013 6994 2015 Smallville 2015 29 2016 19 2015 48 2016