Logic behind loc in pandas

Question

I have some simple code:

for x in range(df2.shape[0]):
   df1.loc[df1['df1_columnA'] == df2.iloc[x]['df2_columnB']]['df1_columnB']

This code goes through the cells located at (iloc[x], df2_columnB) of df2 and when there's a matching value of that cell with df1['df1_columnA'] it accesses that row's value (.loc) at ['df1_columnB'].

My question is, where can I find how this works internally (or if someone would be willing to explain)? Before I knew about this way of comparison I had a couple of nested for loops and other logic to find the values. I've tried searching through the github and other online resources but I can't find anything relevant. I'm simply curious to understand how it compares to my own initial code and/or whether vectorization is used, etc.

Thanks