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Introduction to Data Visualization with Plotly in Python

4.4+
11 reviews
Beginner

Create interactive data visualizations in Python using Plotly.

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4 Hours14 Videos45 Exercises
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Course Description

Producing high-quality, interactive visualizations historically required complex code, extensive time, and effort. Not anymore. In this course, you’ll learn how to create publication-quality graphs harnessing the power of JavaScript, without leaving the comfort of the Python programming language we all love. You’ll create, style, and customize a variety of stunning, interactive graphs—using datasets ranging from stock prices to basketball team stats, and even penguin beak sizes! Using the Plotly charting library, you’ll also learn to customize interactivity such as hover information, range sliders, custom buttons, and even drop-downs that reactively change the visualization. Are you ready to level-up your data visualization skills?
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  1. 1

    Introduction to Plotly

    Free

    Enter the world of Plotly! In this first chapter, you’ll learn different ways to create plots and receive an introduction to univariate plots. You’ll then build several popular plot types, including box plots and histograms, and discover how to style them using the Plotly color options.

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    Plotly and the Plotly Figure
    50 xp
    Playing with a Plotly Figure
    50 xp
    Fixing a Plotly figure
    100 xp
    Univariate visualizations
    50 xp
    Student scores bar graph
    100 xp
    Box plot of company revenues
    100 xp
    Histogram of company revenues
    100 xp
    Customizing color
    50 xp
    What color did we use?
    50 xp
    Coloring student scores bar graph
    100 xp
    Side-by-side revenue box plots with color
    100 xp
    Revenue histogram with stacked bars
    100 xp
  2. 3

    Advanced Customization

    Take your Plotly graphs to the next level with more advanced customizations. Through hands-on exercises, you’ll learn how to layer multiple interactive chart types in the same plot (such as a bar chart with line chart over the top). You’ll then create time-series selectors, such as year to date (YTD), to help you zoom in and out of your line charts.

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  3. 4

    Advanced Interactivity

    In this final chapter, you’ll harness Plotly’s advanced user interactivity as you learn how to create buttons, dropdowns, and sliders that change everything from graph types to annotations and much more. Take your Plotly skills to the next level and build truly interactive user experiences.

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Datasets

Penguins dataRevenue dataAAPL dataWorld Bank population dataSydney temperature dataRainfall dataMonthly salesRevenue Data Extended

Collaborators

Collaborator's avatar
Amy Peterson

Prerequisites

Intermediate Python
Alex Scriven HeadshotAlex Scriven

Senior Data Scientist @ Atlassian

Alex is a Senior Data Scientist working for Atlassian in Sydney, Australia and has previous experience in government, agency and startup. He also holds lecturing and research positions at the University of Technology Sydney and the University of New South Wales. He has built and delivered several Masters-level courses in machine learning & deep learning whilst researching on applications of machine learning & data science in industry. From a heavily commercial background, Alex greatly enjoys bridging the gap between cutting-edge technology and business applications.
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*4.4
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  • José C.
    8 months

    Very interesting!

  • Colin F.
    about 1 year

    The lessons are clearly structured while demanding you learn a wide range of coding skills. The activities can be challenging but the outcome is a rapid increase in knowledge.

  • Ovanes P.
    about 1 year

    I am extremely pleased that I went through this plotly course!!! Will certainly continue to explore aforementioned library capabilities and would like to see more courses in Data Camp regarding this wonderful Plotly. Thank you DataCamp !!!

  • William A.
    over 1 year

    Great introductory course

  • Emiliano R.
    over 1 year

    I need a second part of this course

"Very interesting!"

José C.

"The lessons are clearly structured while demanding you learn a wide range of coding skills. The activities can be challenging but the outcome is a rapid increase in knowledge."

Colin F.

"I am extremely pleased that I went through this plotly course!!! Will certainly continue to explore aforementioned library capabilities and would like to see more courses in Data Camp regarding this wonderful Plotly. Thank you DataCamp !!!"

Ovanes P.

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