Question

当前，我正在使用COVID数据集进行一些分析。

数据集具有以下形式：

    Country Province    Lat Lon         Date                    Cases   Status
0   Thailand        15.0000 101.0000    2020-01-22 00:00:00+00:00   2   confirmed
1   Thailand        15.0000 101.0000    2020-01-23 00:00:00+00:00   3   confirmed
2   Thailand        15.0000 101.0000    2020-01-24 00:00:00+00:00   5   confirmed
3   Thailand        15.0000 101.0000    2020-01-25 00:00:00+00:00   7   confirmed
4   Thailand        15.0000 101.0000    2020-01-26 00:00:00+00:00   8   confirmed

我想按国家/地区分组，汇总“情况”列（我们将其称为“案例总和”列），但是我遇到了经度和纬度问题：我想取最大值的纬度/经度案例栏的内容。换句话说，我希望案例数量最多的那一行的经纬度。要澄清的是，用例是像法国这样的国家/地区中的行经度和纬度都不同（例如，法属波利尼西亚），但是我只想从情况最多的区域中得出经/纬度分组。

我当前正在按照以下方式运行聚合：

nonzero_cases[(nonzero_cases['Date'] == "03/13/2020")].groupby("Country").agg({"Lat":"first","Lon":"first","Cases":"sum"})

这将产生：

Country     Lat     Lon     Cases
Afghanistan 33.0000 65.0000 7
Albania 41.1533 20.1683 33
Algeria 28.0339 1.6596  26
Andorra 42.5063 1.5218  1
...

但这不是我想要的，因为它没有考虑案例编号，只是选择了第一个纬度/经度。

Answer 1

在列Cases上添加DataFrame.sort_values，所以现在第一个值是每组最多Cases的行：

print (df)
    Country   Lat    Lon                       Date  Cases     Status
0  Thailand  15.0  101.0  2020-01-22 00:00:00+00:00      2  confirmed
1  Thailand  15.0  101.0  2020-01-23 00:00:00+00:00      3  confirmed
2  Thailand  15.0  101.0  2020-01-24 00:00:00+00:00      5  confirmed
3  Thailand  15.0  101.0  2020-01-25 00:00:00+00:00      7  confirmed
4  Thailand  14.0  103.0  2020-01-26 00:00:00+00:00      8  confirmed <- changed data

df1 = (df.sort_values('Cases', ascending=False)
         .groupby("Country")
         .agg({"Lat":"first","Lon":"first","Cases":"sum"}))

print (df1)
           Lat    Lon  Cases
Country                     
Thailand  14.0  103.0     25

Answer 2

比jezrael的答案更混乱，但可以完成工作。不幸的是，groupby，np.where，.loc和pd.merge当然是我要研究的50％的熊猫。

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熊猫聚合分组与另一列的最大值？

2 个答案: