Skip to content

Tag: merge

Replace column values between two dataframes according to index

I have a dataframe named calls, each call is recorded by a date (calls)[datetime]. each call has an answer status (calls)[Status]. A second Dataframe named NewStatus with same colum (NewStatus )[datetime] and the column (NewStatus )[New_Status] that I want to replace in the first dateframe with a date join Desired result is the following for calls : By using I

How to efficiently join a small table to a large one on python

I have two tables similar to these: My goal is to multiply df[‘x’] by df[‘y’] based on id. My current solution works, but it seems to me that there should be a more efficient/elegant way of doing this. This is my code: Answer You can use map to recover the multiplication factor from df_2, then mul to the x column:

python3 join lists that have same value in list of lists

I have similar question to one that has been asked several years ago, the link is down here. the thing is that all answers are in python 2 and does work for me. my lists are huge so time is important. if anyone can solve that for python3, that will really help. Consider this list of lists: I want to

Merge dataframes with mirrored values

I have a dataframe which stores measurement points of an circular area. So each point has a Radius_mm and Angle_deg value. As a visual representation of the data, I would now like to create a section through the surface. I.e. I choose one angle and the corresponding angle that lies at 180° to it, including the center. The x-axis should

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