基于多列和一列和的数据帧重排序

Question

我有福勒。数据帧：

              Country_FAO            type   mean_area
0             Afghanistan             car   2029000.0
1             Afghanistan             car    112000.0
2                 Algeria             bus    827000.0
3                 Algeria             bus      2351.0
4               Australia             car   6475695.0
5               Australia             car  12141000.0
6               Australia             bus    293806.0

我想根据mean_area列中每个值的Country_FAO和对这个数据帧重新排序。最终结果如下：

              Country_FAO            type   mean_area
0               Australia             car  12141000.0
1               Australia             car   6475695.0
2               Australia             bus    293806.0
3             Afghanistan             car   2029000.0
4             Afghanistan             car    112000.0
5                 Algeria             bus    827000.0
6                 Algeria             bus      2351.0

澳大利亚排在第一位，因为它的3个类别的mean_area值之和最高。你知道吗

我试过这个：

df_stacked.sort(['Country_FAO', 'mean_area'], ascending=[False, False])

但这不起作用，它不会在进行排序之前将所有的mean_area相加。你知道吗

Answer 1

我认为您需要通过^{}和^{}以及^{}创建新的列sort。最后你可以用^{}来^{}它：

df['sort'] = df.groupby('Country_FAO')['mean_area'].transform(sum)

df['sort'] = df.groupby('Country_FAO')['mean_area'].transform(sum)

df1 = df.sort_values(['sort','Country_FAO', 'mean_area'], ascending=False)
print df1
   Country_FAO type   mean_area        sort
5    Australia  car  12141000.0  18910501.0
4    Australia  car   6475695.0  18910501.0
6    Australia  bus    293806.0  18910501.0
0  Afghanistan  car   2029000.0   2141000.0
1  Afghanistan  car    112000.0   2141000.0
2      Algeria  bus    827000.0    829351.0
3      Algeria  bus      2351.0    829351.0

df1 = df1.drop('sort', axis=1).reset_index(drop=True)
print df1
   Country_FAO type   mean_area
0    Australia  car  12141000.0
1    Australia  car   6475695.0
2    Australia  bus    293806.0
3  Afghanistan  car   2029000.0
4  Afghanistan  car    112000.0
5      Algeria  bus    827000.0
6      Algeria  bus      2351.0