What is Plotly?

Plotly is a versatile software tool designed for data scientists and engineers to build, scale, and deploy data apps with ease. Written in Python, it supports the creation of low-code Python data apps, ensuring a more efficient development process. Its stateless architecture allows for deployment on various cloud platforms, including AWS, Azure, and GCP, providing flexibility and scalability to users.

As a service, Plotly stands out as a low-code platform, enabling the construction of data apps in Python. It boasts a large community and usage, evidenced by its 97,000+ GitHub stars and millions of monthly downloads of its open-source libraries. Plotly's Dash Enterprise platform specifically caters to the rapid development of data-science apps, offering Dash apps which enable users to integrate a point-&-click interface to Python models, effectively bridging the gap between data science and application development.

Regarding data types, Plotly excels with its figures—charts, plots, maps, and diagrams—that are carefully constructed using data structures known as figures. These figures are organized as trees with named nodes, or \"attributes\", including three top-level attributes: data, layout, and frames. The data attribute consists of a list of dictionaries referred to as \"traces\", which are compatible with various subplot types, facilitating the creation of complex and informative visualizations.

Plotly Plugins for Excel Tutorial

Making Charts with Chart Studio and Excel

The tutorial demonstrates several types of visualizations that can be created by integrating Chart Studio with Excel. Users can learn how to make a variety of charts including pie charts, stacked bar charts, grouped bar charts, dot plots, and bar charts. Additionally, the tutorial covers the creation of more complex chart types such as area charts, bubble charts, and time series with error bars.

Advanced Charting Techniques

Beyond basic chart types, the tutorial also instructs on how to create Pareto charts, add shaded regions to charts, and construct histograms and box plots. These advanced techniques allow for more nuanced data representation and can aid in more in-depth data analysis.

Geospatial Data Visualization

For those interested in mapping data geographically, the tutorial includes guidance on making scatter plots with a map, choropleth maps, and bubble maps. These visual tools are essential for presenting data with a spatial component in an informative and visually appealing way.

Complex Chart Structures

The tutorial also shows users how to enhance their data storytelling by creating charts with subplots, inset plots, and multiple axes. These complex structures can provide a more comprehensive view of the data by allowing multiple related visualizations to be presented in a cohesive manner.

Creating Dashboards

Finally, the tutorial explains the process for using Chart Studio to make online dashboards with Excel. This is particularly useful for sharing interactive visualizations and providing access to real-time data insights through an online platform.

Common Use Cases

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  Automating the creation and insertion of interactive, open-source plots into Excel reports
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  Generating and exporting pivot tables and visualizing them graphically within Excel
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  Creating complex visualizations such as heatmaps and integrating them into interactive dashboards
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  Scheduling automated Excel report updates on a daily, weekly, or monthly basis
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  Enhancing Excel reporting efficiency and accuracy through automated formatting tasks like setting borders and column alignment

Frequently Asked Questions

How do I convert Plotly figures to images for Excel?

Plotly figures must be converted to an image using Plotly's write_image method. This process requires the kaleido package, which can be installed via pip or conda.

What should I do if I encounter issues exporting SVG images to Excel?

If there are issues with exporting SVG images, PyXLL allows the use of PNG format for exporting images by passing allow_svg=False.

Can I create interactive Plotly charts in Excel?

You can create semi-interactive plots in Excel by adding arguments to worksheet functions, which allow the plot to be redrawn when arguments change.

Why does exporting a Plotly image to Excel take time when done for the first time?

Exporting an image from Plotly for the first time may take a few seconds as it may involve the launching of a kaleido or orca subprocess.

Why might my antivirus software warn me when exporting a Plotly figure to an image?

Exporting a figure to an image may trigger anti-virus software warnings due to the launching of a kaleido or orca subprocess, which is a necessary part of the image conversion process.