擅长:python、mysql、java
<p>解决这个问题的更一般的方法是对两个表执行类似SQL的连接。你知道吗</p>
<p><strong>注意</strong>:对于较大的数据集,这可能会很昂贵,我还没有尝试过性能。你知道吗</p>
<pre><code>import pandas as pd
left = pd.DataFrame({"UniProtID": ["Q15173", "P30154", "P63151"],
"Name": ["PPP2R5B", "PPP2R1B", "PPP2R2A"]})
right = pd.DataFrame({"UniProtID": ["Q15173", "P30154", "P63151"],
"UniProt Name": ["Prothrombin", "Epidermal growth factor receptor", "Low affinity immunoglobulin gamma Fc region receptor III-B"],
"Type": ["BiotechDrug", "BiotechDrug", "BiotechDrug"],
"DrugBankID": ["DB00001", "DB00002", "DB00003"]})
result = pd.merge(left, right, on="UniProtID")
</code></pre>
<p>引用:<a href="https://pandas.pydata.org/pandas-docs/stable/merging.html#overlapping-value-columns" rel="nofollow noreferrer">https://pandas.pydata.org/pandas-docs/stable/merging.html#overlapping-value-columns</a></p>