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Questions about In-place memory operations in pandas (1/2)

I was explaining[1] in-place operations vs out-of-place operations to a new user of Pandas. This resulted in us discussing passing objects by reference of by value. Naturally, I wanted to show pandas.DataFrame.values as I thought it shared the memory location of the underlying data of the DataFrame. However, I was surprised with and then sidetracked by the results of the

Build a dask dataframe from a list of dask delayed objects

I have a list of dask delayed objects Portfolio_perfs: Each delayed object is a numpy array of length 2 I want to build the following dataframe without using dask.compute: How can I build this dask dataframe without going through dask.compute? Thank you Answer Since each delayed object is a numpy array, you are interested in da.from_delayed(): Alternatively, it’s possible to

Sudoku backtracking solver bug

Ok, I’ve been scratching my head over this for a few hours now.. My goal was to code a sudoku solver that uses the backtracking method and to show the progress of the algorithm using pygame. For this I have to keep track of the events, I did it by appending them to a list named registre as is shown

Combine all column elements except two particular columns

I want to combine the elements in all columns except two columns, ‘SourceFile’ and ‘Label’. I tried the above code. Which resulted in value error. There is so many columns. So I can’t use Answer col != [‘SourceFile’,’Label’] is syntactically wrong and it gives NameError not the ValueError. First get the columns you don’t want and convert it to set.

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