Description:
There are many specialized charts and other advanced features available in Plotly Chart Studio, which can be used to give life to your data. These include Box and Violin plots to analyze the distribution of values, Candlestick charts to analyze tradeable assets' performance, and map charts to visualize geographical data.
In this course, you'll learn how to work with these chart types, as well as funnel, treemaps, and sunburst charts. You'll also practice sharing plots and charts with collaborators and viewers.
Beyond this, you'll learn how to create a dashboard to group related charts. You'll generate curves, namely a moving average and a fitted curve, to augment some of your charts. You'll then finish my writing some Python code and using it to generate charts from a Python application.
Target Audience:
Duration: 01:44
Description:
This course's focus is on working with the variety of charts available in Plotly Chart Studio - each of which has its use case in terms of the kind of information it conveys best. Upon completion, you'll recognize which chart to choose to best present information the underlying data. You'll begin by working with pie charts, a great way to project the proportion of values represented by individual categories.
You'll then work with scatter plots to visualize relationships between two variables, line charts to analyze sequential data, and histograms to understand a distribution of values. While exploring all of these charts, you'll cover several features that make plots useful and exciting, such as using multiple charts within subplots, adding annotations, and configuring the chart axes.
Target Audience:
Duration: 01:16
Description:
This course serves as an introduction to Plotly's Chart Studio - a handy visualization tool that supports various purposes. You'll start by covering the basics, creating or loading a dataset into a grid. You'll then use that data to generate a chart.
Following from there, you'll practice loading different data source types into Chart Studio, such as CSV files and SQL query results. You'll then create basic visualizations, including a bar graph and a table, and style them to suit your aesthetic requirements and, more crucially, to accurately convey the underlying information in your dataset. Lastly, you'll delve into how to set up a single plot to include multiple charts, allowing users to analyze data along various dimensions.
Target Audience:
Duration: 01:16