Last week saw the exciting release of version 3 of the QGIS DataPlotly plugin, which incorporates all the work done as a result of our Print Layouts Graphs and Charts crowdfunding campaign crowd funding campaign. Now, beautiful charts and graphs are available directly within QGIS print layouts, and all it takes is the easy installation of the “DataPlotly” plugin from your QGIS install!

In this post we’ll showcase the functionality which has been added during this campaign, and which is available today in the plugin.

UI modernisation and tweaks

First up, during our work on this plugin we’ve invested some time in refreshing the plugin’s UI to ensure it follows all the widget conventions used elsewhere in QGIS. Now, the plugin blends seamlessly into your QGIS window, and all the chart setting widgets behave in just the way you’re used to. We’ve also used this opportunity to fix a number of issues the plugin had when running on hi-dpi displays (such as Apple retina displays)!

Dynamic charting of selected and visible features

If you’ve used earlier versions of the DataPlotly plugin, you’ll likely notice that there’s many new options shown in the screenshot above. Possibly the most exciting of these is the new “Use only selected features” and “Use only visible features” checkboxes. When either of these options are enabled, then your chart will immediately respond to changes in layer selections or changes to the visible map canvas extent respectively. Previously, interactivity in the plugin only went one way (from the chart to the canvas) – but now the charts are truly interactive, and respond dynamically to changes in the canvas too!

Improved handling of “data defined” settings

During the plugin refactoring, we reworked how “data defined” settings are handled within charts. If you’re not familiar with these, “data defined” settings are QGIS’ approach for exposing per-feature control over the map rendering process. In DataPlotly charts, we expose this functionality to allow per-feature control over the chart appearance (e.g., showing different scatter plot dot colors based on feature attributes). The new code uses the same code model as QGIS itself, so data-defined settings in your charts now have full access to the whole suite of QGIS expression functions and variables that you’re used to! Additionally, QGIS data-defined assistants are fully supported in the charts too. Ultimately, this enables some very advanced styling options, such as charts which dynamically change color and appearance on every page of your print atlas…

Charts in print layouts

We’ve previously covered this feature in depth, but the DataPlotly v3 release brings print-layout based charts to the masses! When a chart is inserted into a print layout, some additional options are available for controlling the plot behavior:

These new options allow you to link the chart to a map item within the layout, which lets you filter the content of the chart to only include features visible within the map. If your print layout is setup as an atlas export, you can also filter out included features to only show those which are geographically located inside the current atlas feature.

Our partners from Faunalia demonstrate this in the screencast below:

Saving plot configuration

An often-requested functionality previous missing from the plugin was the ability to save and restore plot configuration. Now, plot configuration is automatically saved within your QGIS project and restored when you reopen the project. You no longer have to re-create all your charts from scratch at every session (ouch!). We also added the ability to export chart configuration to XML files, allowing you to share and reuse chart configuration across projects.

Behind the scenes work

Aside from all the wonderful new features added to the plugin, we’ve extensively refactored most of the plugin backend. Unit tests and CI infrastructure have been added, which will ensure the plugin remains stable and regression-free in future releases. The code cleanup and simplification has drastically lowered the barrier of contribution to the project, and we’ve already seen new contributors adding more new features to the plugin as a result of this! (Kudos to Simon Gröchenig, who added the new “Feature subset” expression option you can see in the above screenshots!).

Project sponsors

All this work is thanks to the backers of our crowdfunding campaign. Without their contributions this work would not have been possible! In no particular order, our thanks go out to:

• Federico Gianoli
• Papercraft Mountains
• Liam McCrae
• Henry Walshaw
• Raúl Sangonzalo
• Ferdinando Urbano
• pitsch-ing.ch
• Carbon-X
• Gabriel Diosan
• Rene Giovanni Borella
• Enrico Bertonati
• Guido Ingwer
• David Addy
• Gerd Jünger
• Andreas Neumann
• Stefano Campus
• Michael Jabot
• Korto
• Enrico Ferreguti
• Carlo A. Nicolini
• Salvatore Fiandaca
• Alberto Grava
• Hans van der Kwast
• Ben Hur Pintor
• Silvio Grosso
• Nobusuke Iwasaki
• Alasdair Rae
• Manori Senanayake
• Canton de Neuchâtel
• Matthias Daues
• Alteri Seculo
• SunGIS Ltd.
• Stu Smith
• Keolis Rennes
• Gabriel Diosan
• Aiden Price
• Giacomo Ponticelli
• Diane Fritz
• Gemio Bissolati
• Claire Birnie
• Nicolas Roelandt
• Rocco Pispico
• Gabriel Bengtsson
• Birds Eye View
• Barend Köbben
• Roberto Marzocchi (GTER)
• Yoichi Kayama
• Alessandro Sarretta
• Luca Angeli
• Luca Bellani
• giswelt
• Stefan Giese
• Ben Harding
• Joao Gaspar
• Romain Lacroix
• Ryan Cooper
• Daniele Bonaposta
• QGIS Swedish User Group
• Nino Formica
• Michael Gieding
• Amedeo Fadini
• Andrew Hannell
• Stefano
• Phil Wyatt
• Brett Edmond Carlock
• Transitec

Keep an eye out on the North Road blog for future crowd-funding initiatives. Coming soon: a QGIS Processing grab-bag of ETL modelling improvements!

If you’ve been following our latest updates, you’ll be well aware that North Road and Faunalia are running a crowd funding campaign to add rich charting and graph functionality to QGIS’ Print Layout designer. This missing feature is a large gap in QGIS printing capabilities, so we’re planning on filling that gap by exposing the powerful QGIS “Data Plotly” plugin to allow these charts to be embedded inside your layouts, and allow them to be created and modified in a simple, interactive style. And thanks to a large group of generous backers, the campaign is off to a fantastic start!

Accordingly, we’d like to take the opportunity to showcase some of the current plot styles available from the QGIS DataPlotly plugin, all of which will be possible to insert into your print layouts if the campaign is successful. Let’s start with the default chart option – a simple scatter plot:

In this screenshot we see a scatter plot of Educational Usage vs Distance from City for a network of railway stations. We’ve left most settings at their default in order to illustrate that even out-of-the-box, the charts look great! They’ll fit right alongside your map masterpieces in your print layouts and won’t look out of place. It’s also important to note that the above screenshot demonstrates the current interactive canvas mode for the DataPlotly plugin. If this campaign is successful, the chart designer shown above will be available directly inside the QGIS Print Layout designer window. Users will be able to drop new charts into their layouts, and then edit the properties of those charts in a interactive manner. Exciting stuff indeed!

So what other plot styles are currently available in DataPlotly? Here’s a quick showcase of what’s hopefully in the future for QGIS’ print layouts…

Box plots

Bar plot

Histograms

Pie Charts

2D Histogram

Polar Plots

Ternary Plots

Contour Plots

Violin Plots

These plots can already be created from your map canvas using the version of DataPlotly available from the standard QGIS plugin repository, so we encourage you to download the plugin and have a play, and start to get a feel for the flexibility and power having access to these charting options will bring to your print layouts!

You can help make this feature a reality by supporting the campaign or by sharing the page and increasing exposure to the campaign. Full details about the planned functionality and how to contribute are available at the campaign page.

Ever wished QGIS had a way to insert dynamic, feature rich charts and graphs directly inside print layouts? If so, our latest crowdfunding campaign has you covered! This missing feature is a large gap in QGIS printing capabilities, so we’re planning on filling that gap by exposing the powerful QGIS “Data Plotly” plugin to allow these charts to be embedded inside your layouts, and allow them to be created and modified in a simple, interactive style.

If you’re not aware of the existing capabilities of the DataPlotly plugin, here’s a quick screencast which should get you excited about the possibilities here…

QGIS is already a reporting powerhouse, and we believe that linking DataPlotly with QGIS print layouts will boost the current functionality up an order of magnitude! To make it possible we need 8600€ pledged before 30 April 2019. North Road is collaborating on this campaign with our friends at Faunalia, and development work will be shared between the two consultancy firms.

You can help make this a reality by supporting the campaign or by sharing the page and increasing exposure to the campaign. Full details about the planned functionality and how to contribute are available at the campaign page.