Python has an integer type, a float type, and a complex type; however, this is not enough for scientific computing. In practice, we need even more data types with varying precision, and therefore, different memory size of the type. For this reason, NumPy has a lot more data types. The majority of NumPy numerical types end with a number. This number indicates the number of bits associated with the type. The following table (adapted from the NumPy user guide) gives an overview of NumPy numerical types: