Numpy is a python library used for computing scientific/mathematical data.

Numpy usages are in: Numerical Analysis Linear algebra Matrix computations Including the above concepts, Numpy provides an important feature called Arrays Even though it is similar to python List, Array has advantages over List. Advantages of Arrays are: Memory Efficient Faster Convenient Below is the code to create a new Numpy Array. The array() method takes a list of items that go into the array.

Learn about NumPy Array, NumPy Array creation, various array functions, array indexing & Slicing, array operations, methods and dimensions,It also includes array splitting, reshaping, and joining of arrays. Even the other external libraries in Python relate to NumPy arrays.

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How to Create Numpy Arrays? A quick overview about different ways of creating numpy arrays

The content present in the NumPy arrays can be made accessible, and also we can make changes thorough indexing as we got to know in the previous module. Another way of data manipulation in arrays in NumPy is though slicing through the arrays. We can also try changing the position of the elements in the array with the help of their index number. Slicing is the extension of python’s basic concept of changing position in the arrays of N-d dimensions.

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