<p>您可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.map.html" rel="nofollow noreferrer">^{<cd1>}</a>方法:</p>
<pre><code>dfout['EXCHANGE_RATIO'] = dfout['CURRENCY'] \
.map(dict(zip(dfc['CURRENCY_SOURCE'], dfc['EXCHANGE_RATIO'])))
</code></pre>
<p>例如,像这样的<code>dfout</code>:</p>
<pre><code> DATE_PROCESS BOOKING_ID DEP_AIRPORT ARR_AIRPORT DEPARTURE_DATE ARRIVAL_DATE PRICE CURRENCY
0 2013-04-19 16:04:13 UTC 76969972 AEL DEL 2013-04-18 00:00:00 NaN 409.04 EUR
1 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 EUR
2 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 TRL
3 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 VES
</code></pre>
<p>您将获得以下输出:</p>
<pre><code> DATE_PROCESS BOOKING_ID DEP_AIRPORT ARR_AIRPORT DEPARTURE_DATE ARRIVAL_DATE PRICE CURRENCY EXCHANGE_RATIO
0 2013-04-19 16:04:13 UTC 76969972 AEL DEL 2013-04-18 00:00:00 NaN 409.04 EUR NaN
1 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 EUR NaN
2 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 TRL 9.900000e-08
3 2014-04-17 02:26:46 UTC 76888867 ARP ZAL 2014-04-19 00:00:00 NaN 280.70 VES 3.220000e-07
</code></pre>
<p>如果你想替换那些<code>NaN</code>,你可以使用<code>fillna()</code>:</p>
<pre><code>dfout['EXCHANGE_RATIO'] = dfout['CURRENCY'] \
.map(dict(zip(dfc['CURRENCY_SOURCE'], dfc['EXCHANGE_RATIO']))) \
.fillna(1) # or whatever you want there
</code></pre>