我想在 df 数据帧中将国家/地区代码表示为 df2 数据帧的字段Nationality_Codes中的alpha_3_code。对于 df2 中的每一行，我想将Reviewer_Nationality与 df 中的en_short_name匹配，如果匹配，则在 df2 中为Nationality_Codes分配国家/地区代码。
df2.head()
Nationality_Codes Reviewer_Nationality Reviewer_Score
NaN Russia 2.9
NaN United Kingdom 7.5
NaN Australia 7.1
NaN United Kingdom 3.8
NaN Russia 6.7
df.head()
alpha_3_code en_short_name nationality
RUS Russia Russian
ALA Åland Islands Åland Island
ALB Albania Albanian
AUS Australia Australian
UK United Kingdom British, UK
最终结果应该是：
df2.head()
Nationality_Codes Reviewer_Nationality Reviewer_Score
RUS Russia 2.9
UK United Kingdom 7.5
AUS Australia 7.1
UK United Kingdom 3.8
RUS Russia 6.7
我尝试了这段代码，但没有奏效。
for index, row in df.iterrows():
for index2, row2 in df2.iterrows():
if row2['Reviewer_Nationality']==row['en_short_name']:
df2['Nationality_Codes'][row2]=df['alpha_3_code'][row2]
谁能帮我？
非常感谢！
一种方法是为英文名称和代码创建一个系列映射，并使用.map：
#my_map = pd.Series(df.alpha_3_code.values,index=df.en_short_name)
my_map = df.set_index('en_short_name')['alpha_3_code']
df2['Nationality_Codes'] = df2['Reviewer_Nationality'].map(my_map)
输出：
>>> df2
Nationality_Codes Reviewer_Nationality Reviewer_Score
0 RUS Russia 2.9
1 UK United Kingdom 7.5
2 AUS Australia 7.1
3 UK United Kingdom 3.8
4 RUS Russia 6.7
试试这个：
merged = df[['alpha_3_code', 'en_short_name']].merge(df2[['Reviewer_Nationality',
'Reviewer_Score']],
left_on='en_short_name', right_on='Reviewer_Nationality', how='left')]
.rename(columns={'alpha_3_code': 'Nationality_Codes'})
.drop('en_short_name', axis=1)