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Tag: join

pandas join tables on two columns without ordering of values

I would like to achieve what it’s described here: stackoverflow question, but only using standard pandas. I have two dataframes: Fist Second: I want to join the two dataframes such that my final dataframe is identical to the first one, but it has also the book_count column with the corresponding values (and NaN if not available). I already wrote something

add a suffix when col names are similar

I am merging two dataframes and both of them have a col called “man”. After the join, one col is called “man_x” and the second is called “man_y”. Is it possible to append the table name or any other string instead of x, y when column names are the same? After this, If I add another table to this df_merged,

Pandas merge indexing not behaving as expected

I am trying to perform an anti-join in effectively one line. However, my one line solution is not giving me the same results that a receive when breaking up the code into two lines (which behaves as expected). Specifically, the single-line solution results in a dataframe with fewer rows. The goal of my anti-join is to remove any overlap of

How to use JOIN and SELECT AS together in SQLAlchemy?

I have the two following tables. Users Table id name email 32 Hello e@mail.com 23 World p@mail.com Sales Table id SellerId CustomerId Amount 4 32 23 25 I want to join the tables in the following way to get this result. Here I want to only get the entries where customer id is equal to 23. Id SellerId SellerName SellerEmail

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