Python 有没有更有效的方法将贴图应用于熊猫系列？

在我的数据框中有一列名为“State”。它包含美国各州的缩写。我有硬编码的地区，我想为每个州创建一个包含地区的新列

我使用了pd.Series.apply（），但是我想知道对于这种类型的映射是否有更好的实践。关于如何改进代码有什么建议吗

这是我目前有效的代码，但我只是对最佳实践的建议持开放态度

def get_region(s, *regions):
    if s in regions[0]:
        return 'west'
    elif s in regions[1]:
        return 'midwest'
    elif s in regions[2]:
        return 'south'
    elif s in regions[3]:
        return 'northeast'
    else:
        return None

west = ['WA','OR','CA','ID','NV','MT','WY','UT','AZ','CO','NM']
midwest = ['ND','MN','WI','MI','SD','NE','KS','IA','MO','IL','IN','OH']
south = ['TX','OK','AR','LA','MS','TN','KY','AL','GA','FL','SC','NC','VA','WV','MD','DE']
northeast = ['PA','NJ','NY','CT','MA','RI','VT','NH','ME']

regions = [west,midwest,south,northeast]

full_df['Region'] = full_df['State'].apply(get_region, args=regions)
full_df['Region'].head(15)

Out:
0          west
1       midwest
2         south
3         south
4       midwest
5          west
6         south
7         south
8          west
9       midwest
10        south
11    northeast
12    northeast
13         west
14         west
Name: Region, dtype: object

---

您可以尝试创建dict并将其映射到列：

west_dict = {i:"west" for i in west}
midwest_dict = {i:"midwest" for i in midwest}
south_dict = {i:"south" for i in south}
northeast_dict = {i:"northeast" for i in northeast}
d = {**west_dict, **midwest_dict, **south_dict, **northeast_dict}
full_df['Region'] = full_df['State'].map(d)

---

查看地图

map

s=pd.DataFrame([west,midwest,south,northeast],index=['west','midwest','south','northeast'])
s=s.reset_index().melt('index')
full_df['Region'] = full_df['State'].map(dict(zip(s['value'],s['index'])))

---

你在寻找效率，因为它应该运行得更快？还是使用更少的代码？运行更快或更少的代码。我真的只是在寻找最佳的编码实践，我想这应该是运行速度更快和代码更少的组合。“更少的代码”！->“最佳实践”我在一行中使用了您所做的一切创建了d，并将其映射到了d，但您的答案更具可读性。非常感谢。伟大的是的，我是为了清晰起见，但总的来说，它肯定可以减少到更少的行。谢谢！非常有效，我现在知道了。melt（）的作用！