Data Visualization Basics with Python
Tips, Techniques, and Best Practices for Effective Chart Visualizations with matplotlib
By Randy Olson
Publisher: O'Reilly Media
Final Release Date: January 2016
Run time: 1 hour 0 minutes

In this Data Visualization Basics with Python training course, expert author Randy Olson will teach you how to create effective data visualizations in Python. This course is designed for users that already have some experience with programming in Python.

You will start by learning about the basics of data visualization, including types of charts, common pitfalls and good practices in data visualization, and data sources. Finally, Randy will teach you about matplotlib, including how to use matplotlib in the Jupyter Notebook, matplotlib styles, and subplots and small multiples.

Once you have completed this computer based training course, you will have learned a number of tips, tricks, and best practices for creating effecting data visualizations in Python. Working files are included, allowing you to follow along with the author throughout the lessons.

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oreillyData Visualization Basics with Python
 
4.4

(based on 10 reviews)

Ratings Distribution

  • 5 Stars

     

    (6)

  • 4 Stars

     

    (2)

  • 3 Stars

     

    (2)

  • 2 Stars

     

    (0)

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    (0)

80%

of respondents would recommend this to a friend.

Pros

  • Accurate (9)
  • Easy to understand (9)
  • Helpful examples (8)
  • Concise (7)
  • Well-written (4)

Cons

No Cons

Best Uses

  • Novice (8)
  • Student (7)
    • Reviewer Profile:
    • Developer (4), Designer (3), Sys admin (3)

Reviewed by 10 customers

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(1 of 1 customers found this review helpful)

 
3.0

Too little information for the price

By Ilya

from Russia

Verified Reviewer

Pros

  • Accurate
  • Easy to understand

Cons

  • Not comprehensive enough
  • Too basic

Best Uses

    Comments about oreilly Data Visualization Basics with Python:

    Course covered the very basics of data visualization, from aesthetics to implementation details. Contains an medium-sized article worth of information, which is too much for the asking price in my opinion.
    Course materials include a very useful "select graph type for the data you want to visualize" instruction.

    (3 of 4 customers found this review helpful)

     
    3.0

    Good but WAY to expensive for what it is

    By Almost

    from Australia

    About Me Developer

    Verified Buyer

    Pros

    • Accurate
    • Concise
    • Easy to understand
    • Helpful examples
    • Well-written

    Cons

    • Not comprehensive enough
    • Too basic

    Best Uses

    • Novice
    • Student

    Comments about oreilly Data Visualization Basics with Python:

    Content was pretty good, well presented and easy to understand but way overpriced! This was like an hour of video for the price of a whole course compared to many places.

    (2 of 2 customers found this review helpful)

     
    5.0

    good presentation for such a big topic

    By Amit

    from Horsham, PA

    About Me Developer

    Verified Buyer

    Pros

    • Accurate

    Cons

      Best Uses

      • Expert

      Comments about oreilly Data Visualization Basics with Python:

      I liked the presentation style and the usefulness of the video for my job

      (2 of 3 customers found this review helpful)

       
      5.0

      A concise but dense introduction to visualization principles

      By Alberto Cairo

      from Miami, FL

      About Me Designer, Educator

      Verified Reviewer

      Pros

      • Accurate
      • Concise
      • Easy to understand
      • Helpful examples
      • Well-written

      Cons

        Best Uses

        • Novice
        • Student

        Comments about oreilly Data Visualization Basics with Python:

        This is a great tutorial that outlines the core principles of data visualization. It is short but thorough. The sections on storytelling, color, and type are quite nice and useful for researchers and scholars, who usually lack training in visual design. This is a big problem, as it leads to many presentation slides, articles, and other kinds of documents that are ugly and unreadable. Design matters if you want to communicate effectively, regardless of your audience, and this video helps with that.

        (I have a few small quibbles, though. For instance, I don't believe that thinking about the story first and looking at the data second is a good strategy. The process is much more complicated, messy, and interesting than that: You can certainly begin with a rough idea of what you want to tell with your charts, but this idea will necessarily change --dramatically so, in many cases-- once you explore the data.)

        All in all, in around one hour you will understand elementary visualization rules and how to apply them with Python. How great is that?

        (4 of 4 customers found this review helpful)

         
        5.0

        A short and sweet introduction

        By TheCthulhuKid

        from Vienna, Austria

        About Me Developer

        Verified Reviewer

        Pros

        • Accurate
        • Easy to understand
        • Helpful examples
        • Well Narrated

        Cons

          Best Uses

          • Novice

          Comments about oreilly Data Visualization Basics with Python:

          Being as stylistically challenged as I am I decided to pick this up to see if I could get any pointers. Really quite glad I did!

          The course is presented by Randal S. Olson who seems to be very comfortable in his role. I usually dislike courses where the presenter remains unseen but here I barely noticed.

          Although the course has its name in the title, Python only comes around in the latter half of the short course. Sometimes I find things like that annoying but here it made perfect sense.

          The first half of the material concerns itself with the very basics. How you can tell stories with data and what stories you might wish to tell. It discusses the types of chart you might wish to use. Common pitfalls and best practices are mentioned.

          I particularly liked that Olson drew attention to colour blindness and offered advice on how to make your charts accessible.

          A nice list of resources for datasets on which to practice is also provided.

          The second half of the material works with Jupyter notebooks to give examples of how individual chart types are implemented. Olson explains how each chart is plotted and the various options available.

          Throughout the course Olson takes care to recommend that you practice with the examples in the accompanying notebooks.

          The videos are bright and the O'Reilly design goes well with the narration. The slides used are done so to good effect. They accent what you hear and are not cluttered with information. The entire course flows well and is easy to follow.

          At one hour you are not going to get an in depth look at data visualisation, but what you do get is an excellent insight as to what is possible.

          (3 of 3 customers found this review helpful)

           
          4.0

          Great intro, useful tips for experts

          By jscarto

          from Annapolis, MD

          About Me Designer

          Verified Reviewer

          Pros

          • Accurate
          • Concise
          • Easy to understand
          • Helpful examples
          • Well-written

          Cons

            Best Uses

            • Intermediate
            • Novice
            • Student

            Comments about oreilly Data Visualization Basics with Python:

            I use Python for data visualization daily, and have use Python nearly a decade. This course was a refreshing view at some familiar concepts and even introduced me to a few new things, or ways to do things more efficiently. I really enjoyed the overview of mplstyles and how to streamline a consistent look and feel.

            While not explicitly an intro to Jupyter, I also found this course a good overview of the utility of notebooks as well.

            Even if you use Python for things aside from visualization, there are a lot of nifty tips and tricks in this course that make it valuable. I highly recommend it to those new to data visualization in Python, and would encourage seasoned experts to give it a look as well.

            I would have liked the portion on color in visualization to be a bit more thorough. It does a good job covering the issue of colorblindness, but the usual rainbow color schemes are still problematic to those with typical vision.

            All in all, this is a solid course and the effort Randy put into this really shows.

            (4 of 4 customers found this review helpful)

             
            5.0

            Great intro for dataviz beginners!

            By Seth

            from Portland, OR

            About Me Data Scientist, Designer

            Verified Reviewer

            Pros

            • Concise
            • Easy to understand
            • Helpful examples
            • Well-written

            Cons

              Best Uses

              • Novice
              • Student

              Comments about oreilly Data Visualization Basics with Python:

              This series of shorts lessons is a perfect intro to data visualization for people new to the field. It covers both aesthetic and technical issues related to proper visualization techniques, and is delivered clearly at a good pace. If you're not interested in matplotlib, the early lessons are still valuable as an introduction on how to select graph types and make a compelling story with your visualizations. Knowing some python is helpful, but not necessary, especially if you are already familiar with something like ggplot2.

              I was given free access to this course in order to provide an honest review.

              (3 of 3 customers found this review helpful)

               
              5.0

              A great combination of best practices and tools!

              By Sebastian

              from East Lansing, MI

              About Me Developer, Educator, Maker, Sys Admin

              Verified Reviewer

              Pros

              • Accurate
              • Concise
              • Easy to understand
              • Helpful examples

              Cons

                Best Uses

                • Novice
                • Student

                Comments about oreilly Data Visualization Basics with Python:

                What I really liked about this course is that it's not only about the "how to" in terms of using Python & matplotlib, there's also a strong focus on the best practices for creating effective visualizations in general -- the main goal of a data visualization is to tell a story.

                In the first half, Randy covers all the important aspects and best practices like the data-ink ratio, when and why to use a particular chart type, chart aesthetics, color schemes, how to accommodate for color blindness and b/w print outs and so forth.

                The second half is then all about creating effective visualizations in matplotlib. Without going into the boring, nitty-gritty details, Randy covers essentially everything you need to know to get started.
                Although, matplotlib is still the most popular and flexible plotting library for Python, it gained a bad reputation for its rather "ugly" looking default styles. In any case, I was really delighted to see that Randy explained the new "styles" that have been added in the recent release, which allow you to create truly beautiful plots.

                PS: As a nice goodie, Randy uploaded the course material -- the IPython notebooks as well as the awesome chart selector (a flow chart that helps you choose the right kind of plot to tell your story!) to a GitHub repository, you should check it out: https://github.com/rhiever/python-data-visualization-course.

                (1 of 1 customers found this review helpful)

                 
                4.0

                Definitely worth your time

                By adamo

                from Athens, Greece

                About Me Sys Admin

                Verified Reviewer

                Pros

                • Accurate
                • Concise
                • Easy to understand
                • Helpful examples

                Cons

                  Best Uses

                  • Novice
                  • Student

                  Comments about oreilly Data Visualization Basics with Python:

                  Half of the course is not Python related. It is visualisation related regardless of the tool. And this is what I loved most about the course. That is focuses on visualisation and not on tools.

                  The second half of the course shows you how to use matplotlib in order to apply what you learned at the first half. The fact that the lecturer stresses practice ("press pause and do the examples") shows that this is not a course where you just sit and listen, but you have to do stuff to learn stuff.

                  Definitely worth the time (and money). I am going to watch the first half again soon.

                  (1 of 1 customers found this review helpful)

                   
                  5.0

                  A great combination of best practices and tools!

                  By Sebastian

                  from USA

                  About Me Data Scientist, Sys Admin

                  Verified Reviewer

                  Pros

                  • Accurate
                  • Concise
                  • Easy to understand
                  • Helpful examples
                  • Up To Date

                  Cons

                    Best Uses

                    • Novice
                    • Student

                    Comments about oreilly Data Visualization Basics with Python:

                    What I really liked about this course is that it's not only about the "how to" in terms of using Python & matplotlib, there's also a strong focus on the best practices for creating effective visualizations in general -- the main goal of a data visualization is to tell a story.

                    In the first half, Randy covers all the important aspects and best practices like the data-ink ratio, when and why to use a particular chart type, chart aesthetics, color schemes, how to accommodate for color blindness and b/w print outs and so forth.

                    The second half is then all about creating effective visualizations in matplotlib. Without going into the boring, nitty-gritty details, Randy covers essentially everything you need to know to get started.
                    Although, matplotlib is still the most popular and flexible plotting library for Python, it gained a bad reputation for its rather "ugly" looking default styles. In any case, I was really delighted to see that Randy explained the new "styles" that have been added in the recent release, which allow you to create truly beautiful plots.


                    PS: As a nice goodie, Randy uploaded the course material -- the IPython notebooks as well as the awesome chart selector (a flow chart that helps you choose the right kind of plot to tell your story!) to a GitHub repository, you should check it out: https://github.com/rhiever/python-data-visualization-course.

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