NumPy for Data Scientist
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- Multi-dimension array creation and perform the processing on multidimensional array
- Indexing of array
- Statistical functions
- Linear Algebra
- Matrix Operations and many more
- Basic knowledge of Python Programming
NumPy stands for numeric python which is a python package for the computation and processing of the multidimensional and single dimensional array elements.
With the revolution of data science, data analysis libraries like NumPy, SciPy, Pandas, etc. have seen a lot of growth. With a much easier syntax than other programming languages, python is the first choice language for the data scientist.
NumPy provides a convenient and efficient way to handle the vast amount of data. NumPy is also very convenient with Matrix multiplication and data reshaping. NumPy is fast which makes it reasonable to work with a large set of data.
There are the following advantages of using NumPy for data analysis.
NumPy performs array-oriented computing.
It efficiently implements the multidimensional arrays.
It performs scientific computations.
It is capable of performing Fourier Transform and reshaping the data stored in multidimensional arrays.
NumPy provides the in-built functions for linear algebra and random number generation.
Nowadays, NumPy in combination with SciPy and Matplotlib is used as the replacement to MATLAB as Python is more complete and easier programming language than MATLAB.
- Want to Learn Data Science
- Beginner Python Developer