NumPy Python Tutorial - Part 1 | NumPy and Pandas Tutorial | NumPy Tutorial | NumPy Introduction
NumPy Python Tutorial - Part 1 | NumPy and Pandas Tutorial | NumPy Tutorial | NumPy
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Hello and welcome to NumPy python tutorial powered by Acadgild. Let’s start with NumPy basics.
There are basic libraries which are really important for the data manipulation. So, first is ‘NumPy’ that is nothing but numeric python and then there is ‘pandas’ and then there is ‘scipy’.
So, these three are the basic libraries which are very important for you to learn and these two things are very related the NumPy and pandas they are the core structure to handle the data. So, you need to understand NumPy and pandas when you are going to deal with the data.
What is NumPy?
NumPy is nothing but provides all the libraries to deal with the linear algebra.
• NumPy, which stands for Numerical Python
• NumPy is the foundational package for mathematical computing
• Mathematical and logical operations on arrays
• Operations related to linear algebra. NumPy has inbuilt functions for linear algebra and random generation
• ndarray is the core object in NumPy
Basics ndarray
• Multidimensional array
• Homogeneous collection of values
• Fast and efficient
• Support for mathematical functions
• Primary container for data exchange between python algorithms
Important attributes of an ndarray object are:
• Ndarray.ndlm: the number of axes (dimensions) of the array, the number of dimensions is referred to as rank
• Ndarray.shape: the dimensions of the array. This is tuple of integers indicating the size of the array in each dimension. For a matrix within rows and m columns, the shape will be (n,m)
• Ndarray.size: the total number of elements of the array.this is equal to the product of the elements of shape
• Ndarray.dtype: an object describing the type of the elements in the array
#numpy, #numpytutorial, #pythontutorial, #numpypandas
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