python - 在一行代码中用 pandas 执行多个替换

Question

我想按如下方式更改我的数据:

"Republic of Korea": "South Korea",
"United States of America": "United States",
"United Kingdom of Great Britain and Northern Ireland": "United Kingdom",
"China, Hong Kong Special Administrative Region": "Hong Kong"

目前，我正在使用代码:

energy.Country[energy.Country == "Republic of Korea"] = "South Korea"
energy.Country[energy.Country == "United States of America"] = "United States"
energy.Country[energy.Country == "United
               Kingdom of Great Britain and Northern Ireland"] = "United Kingdom"
energy.Country[energy.Country == "China, 
               Hong Kong Special Administrative Region"] ="Hong Kong"`

我尝试使用 .replace 方法来做同样的事情，将参数作为字典传递:

energy.replace('国家' : {"大韩民国": "韩国",
"United States of America": "美利坚合众国",
"United Kingdom of Great Britain and Northern Ireland": "联合王国",
"中国香港特别行政区": "香港"})

但是好像不行，有没有更干净整洁的方法呢？

Answer 1

在 Series 上调用 replace，这更容易。

repl_dict = {"Republic of Korea": "South Korea", ...}
energy['Country'] = energy['Country'].replace(repl_dict)

请注意，这不是使用 map 的好地方，因为“Country”中没有映射到 repl_dict 中任何内容的条目将被替换为 NaN。

---

另一种选择是基于 list-comp 的替换:

energy['Country'] = [
    repl_dict.get(x, x) for x in energy['Country'].tolist()] 

不像replace那样简洁，但在性能方面绝对非常称职。