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There are a bunch of ways to add a column to a dataframe..
what is the fastest with modin?
say get a new column by applying a function to another one
new_c = df['column'].apply(lambda x: abs(x))
the resulting series should have the same partitions as the dataframe right?
we can use... merge, or concat, or just do
df['new_col'] = new_c
which is the most readable IMO
and probably a few other ways
but what is the fastest?
Thank you!
The text was updated successfully, but these errors were encountered:
And also:
How to add multple columns at once?
concat ? will it play nice with partitions?
cause
df[['col1','col2']] = <some np array with 2 columns and the corrent amount of rows>
just defaults to pandas... because inserting with unhashable key is not supported..?
I dont want to make a new modin dataframe out of the np array for concatenation because i dont want to cause trouble with partitions that dont fit.
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There are a bunch of ways to add a column to a dataframe..
what is the fastest with modin?
say get a new column by applying a function to another one
the resulting series should have the same partitions as the dataframe right?
we can use...
merge, or concat, or just do
which is the most readable IMO
and probably a few other ways
but what is the fastest?
Thank you!
The text was updated successfully, but these errors were encountered: