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Following: https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html This - df.to_numpy() throws an AttributeError: 'DataFrame' object has no attribute 'to_numpy'
Not sure why.
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Pandas tail() method is used to return bottom n (5 by default) rows of a data frame or series.
Numba can be used in 2 ways with pandas: Specify the engine="numba" keyword in select pandas methods. Define your own Python function decorated with @jit and pass the underlying NumPy array of Series or DataFrame (using to_numpy() ) into the function.
Pandas keeps track of data types, indexes and performs error checking — all of which are very useful, but also slow down the calculations. NumPy doesn't do any of that, so it can perform the same calculations significantly faster.
Try df.values instead. This will have the same effect for versions of pandas prior to 0.24.0
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