Python Data Science: After work guide to start learning Data Science on your own. Avoid common beginners mistakes of coding. Approach Panda and NumPy to become a brilliant computer programmer. by CODING HOOD & Michail Kölling

Author:CODING HOOD & Michail Kölling [HOOD, CODING]
Language: eng
Format: azw3
Published: 2020-10-21T00:00:00+00:00

Chapter 4: Visualization with Matplotlib

How to Work with Matplotlib to Create Great Visuals

Another great library that we can work with, especially when we are spending some time working on our own visuals as we talked about before, is the matplotlib library. This is going to be a great option to work with when we handle some of the work that we want to do with a data science project and will ensure that we can take all of the data points, and all of the different predictions that we were able to get with our algorithms and some of the machine learning that we have from earlier, to help us with visuals so that we understand the data a little bit easier.

To start with, the Matplotlib is going to be one of the plotting libraries that is available to work along with the Python programming language. It is also going to be one of the components that come with the NumPy library that we talked about before, big data, and some of the numerical handling resources. Matplotlib uses an API that is more object-oriented to help embed plots in applications of Python as well.

Since Python is going to be used in machine learning in many cases, resources like NumPy and matplotlib are going to be used in many cases to help out with some of the modelings that we need to do with machine learning and to ensure that we can work with these technologies either.

The idea that we are going to get with this one is that the programmer can access these libraries to handle some of the key tasks that are inside of the bigger environment that we have with Python. It is then able to go through and integrate the results with all of the other elements and features of the program for machine learning, a neural network, and some of the other more advanced options that we would like to use.

You will find that some of the utility that we can see with this library, as well as with the NumPy is going to be centered around numbers. The utility of Matplotlib is going to be specifically done with visual plotting tools. So, in a sense, these resources are going t be more analytical rather than generative. However, all of the infrastructures that we can see with this library is going to allow for the programs of machine learning, when we properly use them, can give us the right results for human handlers as well.

With some of this information in mind, we need to look a bit more about the Matplotlib library in more detail. To start with, this is going to be part of the package from Python to help with 2D graphics. Learning how to work with this kind of library efficiently is going to be so important when you would like to handle some of the visuals and more that you want to do in a data science project.

What is Matplotlib?

This is going

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