Detecting differences in a Pandas Dataframe - use of lambdas in .loc[] syntax

Question

I am referring to this article:

I don't understand this particular syntax for loc, where a lambda is doing the row filtering?

df = df1.merge(df2, how = 'outer' ,indicator=True).loc[lambda x : x['_merge']=='left_only']

What is this lambda doing, I know the end result - just trying to understand the use of lambdas in "loc" syntax.

It would make more sense to do it this way and it's also more readable because of query, I don't like the use of lambda for filtering. — Erfan
– Erfan, Commented Jul 27, 2020 at 14:42

GPhilo · Accepted Answer · 2020-07-27 14:40:47Z

3

loc accepts (among other things) a one-argument callable that is called on each row. The callable is expected to return something that can be used as an index (in this case, a boolean).

Effectively, this syntax means "for each row x in the merged dataframes, call the lambda on the row and select it if x['_merge'] == 'left_only'".

answered Jul 27, 2020 at 14:40

GPhilo

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2 Comments

Is there possible to filter result of merge without lambda, and with chaining methods as in example?

Yes. As @Erfan pointed out in the comment to the question, you can use .query('_merge == "left_only"') to obtain the same result.