Nicolas Kruchten
is a data visualization researcher
based in Montreal, Canada.
SciPy 2021: Data Visualization as the First and Last Mile of Data Science
I was proud to be able to give a talk at SciPy 2021 this year, about Plotly Express and Dash!
Remaking Figures from Bertin's Semiology of Graphics
I’ve just published a personal project I’ve been thinking about doing for a few years now: revisiting figures from a 1967 book which has had a big influence on how I (and others!) think about data visualization, Jacques Bertin’s Semiology of Graphics.
Interview on IQT Podcast
I was recently interviewed on the IQT Podcast about Visualizing Data During a Pandemic, and how Plotly is contributing to COVID-19 response.
SciPy 2020: Tools Plenary Session
I was pleased to give a three-minute rundown at SciPy 2020 about what the Plotly.py team has been up to! My bit is at timecode 8:25.
Polytechnique Montréal: Plotly Express & Dash
I was happy to be invited back for a third time to talk about Plotly during Professor Thomas Hurtut's data visualization class at Polytechnique Montréal (in English this time!).
Beyond “tidy”: Plotly Express now accepts wide-form and mixed-form data
Plotly Express is the built-in high-level data visualization interface for Plotly.py, a leading interactive data visualization library for Python. With today’s release of Plotly.py 4.8, Plotly Express now gracefully operates on wide-form and mixed-form data – not just “tidy” long-form data. These new capabilities dramatically expand Plotly Express’ promise of ‘interactive data visualization in a single Python statement’, by removing the need to wrangle your data into a particular form before plotting.
Polytechnique Montréal: Plotly Express & Dash (en français)
I was happy to be invited back to talk about Plotly during Professor Thomas Hurtut's data visualization class at Polytechnique Montréal (in French).
Montreal Python: Plotly Express and Dash
I recently gave a talk about Plotly Express and Dash at Montreal Python. The description of the talk was, "You start the morning exploring some data in a Jupyter notebook with Plotly Express and after lunch you whip up a web application to give your non-programmer colleagues access to those same insights with Dash, all in under a 100 lines of Python, no Javascript required. This talk will show you how Plotly's open-source libraries fit together to make this possible."
Introducing Plotly Express
Plotly Express is a new high-level Python visualization library: it’s a wrapper for Plotly.py that exposes a simple syntax for complex charts. Inspired by Seaborn and ggplot2, it was specifically designed to have a terse, consistent and easy-to-learn API: with just a single import, you can make richly interactive plots in just a single function call, including faceting, maps, animations, and trendlines. It comes with on-board datasets, color scales and themes, and just like Plotly.py, Plotly Express is totally free: with its permissive open-source MIT license, you can use it however you like (yes, even in commercial products!). Best of all, Plotly Express is fully compatible with the rest of Plotly ecosystem: use it in your Dash apps, export your figures to almost any file format using Orca, or edit them in a GUI with the JupyterLab Chart Editor!
Polytechnique Montréal: Intro to Plotly
I was happy to be invited to talk about Plotly during Professor Thomas Hurtut's data visualization class at Polytechnique Montréal (in French).