What are the differences between Pandas and NumPy in Python?

What are the differences between Pandas and NumPy in Python?

Pandas is primarily used for data manipulation and analysis, while NumPy is focused on numerical computations. Pandas provides data structures like DataFrames, which are great for handling tabular data, whereas NumPy offers powerful array objects for efficient numerical operations.

Can you give me an example of when to use each?

Sure! Use Pandas when you need to analyze datasets with labeled axes, like CSV files. Use NumPy for mathematical operations on large arrays, like performing element-wise calculations.

Which one is faster for large datasets?

NumPy is generally faster for numerical operations on large datasets due to its optimized performance with arrays. However, Pandas is more convenient for data manipulation tasks.

Are there any situations where I should use both?

Yes, you can use both together! For instance, you might use Pandas to load and preprocess your data, and then convert it to a NumPy array for complex numerical computations.