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Many thanks to the developer for providing a version of jupyterlab.
While using it, I found that tabnine is very time consuming for completing large data frames.
Here is an example.
df=pd.DataFrame([np.random.choice(['a', 'b', 'c'], 20000) forxinrange(20)]).Tdf. # It will take more than 10 seconds before the complementary information is available
The text was updated successfully, but these errors were encountered:
Many thanks to the developer for providing a version of jupyterlab.
While using it, I found that tabnine is very time consuming for completing large data frames.
Here is an example.
The text was updated successfully, but these errors were encountered: