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Python Data Science basics with Numpy, Pandas and Matplotlib

Partner: Udemy
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Description: Welcome to my new course Python Essentials with Pandas and Numpy for Data ScienceIn this course, we will learn the basics of Python Data Structures and the most important Data Science libraries like NumPy and Pandas with step by step examples! The first session will be a theory session in which, we will have an introduction to python, its applications and the libraries.In the next session, we will proceed with installing python in your computer. We will install and configure anaconda which is a platform you can use for quick and easy installation of python and its libraries. We will get ourselves familiar with Jupiter notebook, which is the IDE that we are using throughout this course for python coding.Then we will go ahead with the basic python data types like strings, numbers and its operations. We will deal with different types of ways to assign and access strings, string slicing, replacement, concatenation, formatting and f strings. Dealing with numbers, we will discuss the assignment, accessing and different operations with integers and floats. The operations include basic ones and also advanced ones like exponents. Also we will check the order of operations, increments and decrements, rounding values and type casting.Then we will proceed with basic data structures in python like Lists tuples and set. For lists, we will try different assignment, access and slicing options. Along with popular list methods, we will also see list extension, removal, reversing, sorting, min and max, existence check , list looping, slicing, and also inter-conversion of list and strings.For Tuples also we will do the assignment and access options and the proceed with different options with set in python. After that, we will deal with python dictionaries. Different assignment and access methods. Value update and delete methods and also looping through the values in the dictionary.
Category: Development > Data Science > Data Science
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Price: 159.99
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Source: Impact
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