Can I use NumPy instead of Pandas?

Yes, you can use NumPy instead of Pandas in certain situations. NumPy and Pandas are both Python libraries commonly used for data manipulation and analysis, but they have different primary purposes and functionalities.

NumPy (Numerical Python) is primarily designed for numerical computations and working with arrays of numerical data. It provides a powerful N-dimensional array object (ndarray) that allows you to perform mathematical operations efficiently. NumPy is widely used for tasks like mathematical computations, linear algebra, random number generation, and working with multi-dimensional data.

Pandas, on the other hand, is built on top of NumPy and provides additional data structures and tools specifically tailored for data manipulation and analysis. The two main data structures in Pandas are the Series (for one-dimensional labeled data) and the DataFrame (for two-dimensional labeled data, similar to a table or spreadsheet). Pandas offers powerful tools for data cleaning, filtering, grouping, merging, and visualization, making it particularly useful for working with structured and tabular data.

So, while NumPy can handle numerical operations and arrays, it lacks the more specialized data manipulation functionalities that Pandas provides. However, for specific tasks where you only need numerical computation and don't require data handling and analysis, you can use NumPy alone. On the other hand, if you are dealing with datasets and require data manipulation and analysis, Pandas will be a more suitable choice due to its higher-level data handling capabilities.