What are the differences between Pandas and NumPy with examples?

Can you explain the differences between Pandas and NumPy with examples?

Sure! Pandas is primarily used for data manipulation and analysis, while NumPy is used for numerical computations. For example, in Pandas, you can easily handle missing data and perform operations on DataFrames, whereas NumPy focuses on array operations.

Can you give me a specific example of how to use both?

Absolutely! In Pandas, you can create a DataFrame like this:

import pandas as pd

data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)

And in NumPy, you can create an array like this:

import numpy as np

array = np.array([[1, 2, 3], [4, 5, 6]])

How would I perform a calculation using both?

You can perform calculations in Pandas using DataFrame methods. For example, to add a new column that is the sum of columns 'A' and 'B':

df['C'] = df['A'] + df['B']

In NumPy, you can perform element-wise operations directly on arrays:

result = array + 10  # Adds 10 to each element

Which one should I use for data analysis?

If your focus is on data analysis and manipulation, Pandas is the better choice due to its powerful DataFrame structure. NumPy is great for numerical computations and when performance is critical.