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source-code/pandas/README.md
@@ -34,3 +34,5 @@ easy to use.
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a comparison of performance between using `apply` and vectorized operations.
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1. `numba_and_pandas.ipynb`: Jupyter notebook that demonstrates how to use Numba
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to optimize performance of operations on pandas dataframes.
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+1. `from_long_to_wide_and_back_again.ipynb`: Jupyter notebook that illustrates
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+ how to reshape data using `stack` and `pivot` methods in pandas.
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