How do Pandas and NumPy compare in terms of speed for data processing?

How do Pandas and NumPy compare in terms of speed for data processing?

Pandas is great for data manipulation and analysis, but NumPy is generally faster for numerical computations. Would you like to see a speed test comparison?

Yes, please provide some examples of speed tests between the two.

Sure! For instance, if you perform element-wise operations on large arrays, NumPy can be significantly faster due to its optimized C backend. In contrast, Pandas excels in handling labeled data.

Can you show me some code snippets for these tests?

Absolutely! Here's a simple example:

import numpy as np
import pandas as pd
import time

# NumPy speed test
array = np.random.rand(1000000)
start = time.time()
result_numpy = array * 2
print('NumPy time:', time.time() - start)

# Pandas speed test
series = pd.Series(array)
start = time.time()
result_pandas = series * 2
print('Pandas time:', time.time() - start)

Thanks! This is really helpful.