Altair Vs Plotly

Customization in Plotly Express vs. Altair. Plotly Express While Plotly Express is easy to use, it also allows for a high degree of customization. Users can tweak almost every aspect of the plot, from colors and labels to the layout and axes. However, more complex customizations might require diving into the lower-level Plotly library, which

Hi everybody. I used to visualize most of my work in matplotlib and Seaborn after trying Bokeh, Plotly, plotnine, among others, but when I discovered Altair I slowly switched to do most of my visualization to Altair! I still use other libraries specially Seaborn, but I just love Altair's features.

One of the key advantages of altair is its emphasis on data-driven visualization design. By allowing users to think about their data first and foremost, Altair facilitates the exploration and altairunderstanding of complex datasets. I compare code to generate plotly, bokeh, and altair output in the post below.

Similarly to plotly, the screenshot below showcases the interactive features of the altair library. By hovering your mouse over the boxplot you can view various parameters of the data.

Both are interactive plotting packages based on underlying javascript libraries. Plotly express sits on top of plotly.py which is a Python wrapper for plotly.js whereas Altair is a wrapper around VegaLite.js which in turn is based on Vega.js. Both plotly.js and Vega are based on the D3 visualization library, which is the standard js viz library.

A quick introduction to Altair Python, Grammar of Data Visualization. Comparison between Altair and Plotly. How Altair is different from Plotly and other dat

Plotly. Plotly is a cross-language utility that can be written in Python, R or Javascript, and there is also a web-based plot creation tool. There appears to be a big development team behind Plotly and there are also some attempts at monetizing the tool, e.g., using their Dash package. It's a bit of a toss-up for me on whether to use Plotly

Altair. Altair is a statistical visualization library for Python. Compared to Matplotlib and Seaborn, Altair is heavier on statistical features. It allows for doing many kinds of data transformations and filtering while creating a visualization. Let's create the same line plot with Altair. import altair as alt

plotly VS Altair Compare plotly vs Altair and see what are their differences. plotly. The interactive graphing library for Python sparkles by plotly Data Visualization Python D3 Plotly plotlyjs Webgl Dashboard Visualization graph-library plotly-dash jupyter-notebook Sparkles regl Declarative Interactive.

On a different note my original post, Altair makes customizations far more streamlined and easier, and much less verbose than if done with Plotly Dash. The tradeoff comes with following certain grammar rules and a more systematic approach in Altair I feel, but for me personally that is the reason I like it more, as it helps me reduce my