擅长:python、mysql、java
<p>我不确定你在问什么,但如果我理解正确,你想做什么实际上是合并两个数据帧,然后你可以执行任何你喜欢的操作</p>
<p><strong>第一条路</strong></p>
<pre><code>df1 = pd.merge(df,ctr, on='Position' index=False)
#Then you can multiply both columns however you like
df1['Visibility'] = df1.apply(numpy.multiply(df['Average monthly searches'] , df['Decay Ctr']), axis=1)
</code></pre>
<p><strong>第二种方式</strong></p>
<pre><code> df1 = pd.merge(df,ctr,on='Position',index=False)
def multiply(x):
for index, row in df1.iterrows():
row['Visibility'] = row['Average monthly searches'] * row['Decay Ctr']
return row['Visibility']
df1 =df1.apply(multiply, axis=1)
</code></pre>