Python 如何根据特定规则将列从一个数据帧添加到另一个数据帧

我正试着把桌子和桌子结合起来

因此，为了创建2个数据帧，我执行以下操作：

url = 'https://www.cia.gov/library/publications/the-world- 
factbook/fields/2127.html'
url2 = 'https://www.cia.gov/library/publications/the-world- 
factbook/rankorder/2004rank.html'
d = {'TOTAL FERTILITY RATE(CHILDREN BORN/WOMAN)':'TFR'}
d2 = {'Country','GDP - PER CAPITA (PPP)':'GDP (PPP)'}
df = pd.read_html(url, header=0)[0].rename(columns=d)
df2 = pd.read_html(url2, header=0)[0].rename(columns=d2)
df['TFR'] = pd.to_numeric(df['TFR'].str[:-31])

现在，我从df2创建一个子数据帧：

df21 = df2[['Country','GDP (PPP)']]

因此，我最终得到了df21，其中包含了国家名称及其GDP。现在，我想比较两个数据框，并根据每个国家的名称（在df和df2中都有一列包含国家名称）为df中的每个国家分配GDP（PPP）值。有什么办法吗

与左连接一起使用或：

---

如果

df2['country']

中的国家/地区值在

df['country']

中不存在，则创建

NaN

：

print (df[df['GDP (PPP)'].isna()])
                     Country   TFR GDP (PPP)
43          Christmas Island   NaN       NaN
44   Cocos (Keeling) Islands   NaN       NaN
78                Gaza Strip  4.13       NaN
154           Norfolk Island   NaN       NaN
165         Pitcairn Islands   NaN       NaN
191                  Somalia  5.80       NaN
198                 Svalbard   NaN       NaN
230                    World  2.42       NaN

df['GDP (PPP)'] = df['Country'].map(df2.set_index('Country')['GDP (PPP)'])
print (df.head())
          Country   TFR GDP (PPP)
0     Afghanistan  5.12    $2,000
1         Albania  1.51   $12,500
2         Algeria  2.70   $15,200
3  American Samoa  2.68   $11,200
4         Andorra  1.40   $49,900

print (df[df['GDP (PPP)'].isna()])
                     Country   TFR GDP (PPP)
43          Christmas Island   NaN       NaN
44   Cocos (Keeling) Islands   NaN       NaN
78                Gaza Strip  4.13       NaN
154           Norfolk Island   NaN       NaN
165         Pitcairn Islands   NaN       NaN
191                  Somalia  5.80       NaN
198                 Svalbard   NaN       NaN
230                    World  2.42       NaN