How to optimize the performance of a `pandas` `DataFrame` using `numexpr` and `Dask`?

Question

I'm working with a large pandas DataFrame and I'm trying to optimize its performance using the numexpr and Dask libraries. I've tried using the numexpr.evaluate() function to perform element-wise operations on the DataFrame, but it's still taking a long time to run.

Here's an example of the code I'm using:

import numexpr
import pandas as pd

df = pd.read_csv('large_data.csv')

# Perform element-wise operation using numexpr
df['new_column'] = numexpr.evaluate('df.column1 + df.column2')

Is there a way to further optimize the performance of this code using Dask or some other method?