重新分配时,按升序对 pandas 系列中的值进行排序不起作用
Sorting values in a pandas series in ascending order not working when re-assigned
我正在尝试按升序对 Pandas 系列进行排序。
Top15['HighRenew'].sort_values(ascending=True)
给我:
Country
China 1
Russian Federation 1
Canada 1
Germany 1
Italy 1
Spain 1
Brazil 1
South Korea 2.27935
Iran 5.70772
Japan 10.2328
United Kingdom 10.6005
United States 11.571
Australia 11.8108
India 14.9691
France 17.0203
Name: HighRenew, dtype: object
值按升序排列。
但是,当我随后在数据帧的 上下文中修改系列时 :
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True)
Top15['HighRenew']
给我:
Country
China 1
United States 11.571
Japan 10.2328
United Kingdom 10.6005
Russian Federation 1
Canada 1
Germany 1
India 14.9691
France 17.0203
South Korea 2.27935
Italy 1
Spain 1
Iran 5.70772
Australia 11.8108
Brazil 1
Name: HighRenew, dtype: object
为什么这给我的输出与上面的不同?
如有任何建议,将不胜感激?
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).to_numpy()
或
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).reset_index(drop=True)
当你 sort_values 时,索引不会改变 所以它是根据索引对齐的!
感谢 anky 为我提供了这个绝妙的解决方案!
我正在尝试按升序对 Pandas 系列进行排序。
Top15['HighRenew'].sort_values(ascending=True)
给我:
Country
China 1
Russian Federation 1
Canada 1
Germany 1
Italy 1
Spain 1
Brazil 1
South Korea 2.27935
Iran 5.70772
Japan 10.2328
United Kingdom 10.6005
United States 11.571
Australia 11.8108
India 14.9691
France 17.0203
Name: HighRenew, dtype: object
值按升序排列。
但是,当我随后在数据帧的 上下文中修改系列时 :
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True)
Top15['HighRenew']
给我:
Country
China 1
United States 11.571
Japan 10.2328
United Kingdom 10.6005
Russian Federation 1
Canada 1
Germany 1
India 14.9691
France 17.0203
South Korea 2.27935
Italy 1
Spain 1
Iran 5.70772
Australia 11.8108
Brazil 1
Name: HighRenew, dtype: object
为什么这给我的输出与上面的不同?
如有任何建议,将不胜感激?
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).to_numpy()
或
Top15['HighRenew'] = Top15['HighRenew'].sort_values(ascending=True).reset_index(drop=True)
当你 sort_values 时,索引不会改变 所以它是根据索引对齐的!
感谢 anky 为我提供了这个绝妙的解决方案!