Pandas and NumPy are two of the most used Python libraries for data manipulation. Most of the times they are used in a single project. Although Pandas is a library build directly off from NumPy, there are some differences between both of them. Differences Pandas NumPy Data input Tabular form - CSV or SQL formats Numerical data Main feature Helps add, edit, or create columns or rows to the table. Helps perform multiple operations on Array. Building block Series which is built off from ndArrays of NumPy. ndArrays - Allow mathematical operations to be vectorized and when compared to Python lists, they are stored with much better efficiency. Ways to access data We can use labeled data - integers as well as numbers to label the elements of the series object. Only integers are used for labeling the elements.