A free video tutorial from Jose Portilla
Head of Data Science, Pierian Data Inc.
4.6 instructor rating • 32 courses • 2,286,927 students
Learn about Data Visualization with Matplotlib and Python!
Learn more from the full coursePython for Data Science and Machine Learning Bootcamp
Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
24:46:41 of on-demand video • Updated May 2020
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
- K-Means Clustering
- Logistic Regression
- Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines
English Hello everyone and welcome to the introduction to lib lecture and this lecture we're going to get a brief introduction of what Matt it is and then show you just a little bit of the Web site from plotless . Matt lib or as some people pronounce it Matt plus libe is the most popular plodding library for Python and it really gives you complete control over almost every aspect of a figure or plot and it's designed to have a very similar feel to Matlab which is another programming language in its own graphical plotting capabilities map plot lib works very well with Pandanus and umpire race which is why we're going to learn about it later on. We're going to learn about some other libraries such as Seaborn that is actually built off of Matt Plup live. But in order to understand those libraries it's important to understand that plot lived First you'll need to install it with either Pipp or Konda at your command line or terminal with one of the following commands for using the Anaconda distribution of python. A simple Konda install Matt Cutlip at your command line or terminal should install that live for you . Or if you using another version of Python Pipp install matplotlib should also work for you. Now let's go ahead and get a quick tour of the official website. Ok here I am at that plot live org which is the official Web site for map plot lym you'll see here there's some introduction information as well as some more official installation instructions and some other documentation links. Probably the most important link on this page however is right here under gallery. If you click on gallery or go to that part live the org slash gallery you'll get taken to this link and you should see a list of a bunch of different types of plot names. And if you keep scrolling down you'll see that there's a bunch of figures or example figures and these are all the various types of plots that Cutlip is capable of creating for you. Later on we'll learn how to use other libraries that are better for things such as the fiscal plots . But if you ever find yourself having a question of that plot lives capabilities you can come to this page and search for the kind of plot you're looking for. For example if I go ahead and scroll back up here let's say you want to make a pie chart. Will you come here and there's a gallery look for where it says pie charts. Click here. High end polar charts. They'll come down to this link and then I'll show you some couple of figures here that are hopefully relevant examples once you find one that looks like what you want to do is go in and click this first one. It will take you to an example page that not only has to figure but also has very well commented code and instructions on how to perform whatever plots you're looking for. In this case a pie chart. All right. So that's probably the most helpful page on that putt. The other links are just basically links to the documentation functions in it. And we're going to go over the most common functions as we continue on throughout this section of the course. All right. Remember that matplotlib org is a resource for you especially the gallery page. Coming up next we're going to show you how to actually use Matt Plett live to create your own figures . Thanks everyone and I'll see you at the next lecture