<p>使用<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.map.html" rel="nofollow noreferrer">^{<cd1>}</a>和<a href="http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.fillna.html" rel="nofollow noreferrer">^{<cd2>}</a>原始列不匹配的repalce值:</p>
<pre><code>s = corrected_df.set_index('Car Brand')['Current City']
original_df['Original City'] = (original_df['Original Car Brand'].map(s)
.fillna(original_df['Original City']))
print (original_df)
Original Car Brand Original City
0 Daimler Chicago
1 Mitsubishi LA
2 Tesla Amsterdam
3 Toyota Zurich
4 Renault Paris
5 Ford Toronto
6 BMW Munich
7 Audi Sport Helsinki
8 Citroen Dublin
9 Chevrolet Brisbane
10 Fiat Detroit
11 Audi Berlin
12 Ferrari Bruxelles
13 Volkswagen Stockholm
14 Lamborghini Rome
15 Mercedes Madrid
16 Jaguar Boston
</code></pre>
<p>您的解决方案应在<code>dict</code>之前将两列转换为numpy数组:</p>
<pre><code>d = dict(corrected_df[['Car Brand','Current City']].to_numpy())
original_df['Original City'] = (original_df['Original Car Brand'].map(d)
.fillna(original_df['Original City']))
</code></pre>