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R is everywhere, especially when you need to visualize stuff. It is primarily used in teams who are trying to get rid of SAS in my experience. You are right in

R is everywhere, especially when you need to visualize stuff. It is primarily used in teams who are trying to get rid of SAS in my experience. You are right in the sense that R is typically not used end-to-end as far as I can tell, but already tries to start with a data connection to some sort of dump or datalake, or datawarehouse. Many people in my team use Python for modelling, but grab ggplot in whatever way to make their presentations and visuals (they all use different methods, usually something messy like mixing python and R in a notebook or so). GGPlots also has a vast library of super high quality plugins. Python is far far behind in the viz space

mrtranscendence 5y ago
There are Python ports of ggplot (e.g. plotnine (https://github.com/has2k1/plotnine https://github.com/has2k1/plotnine)), but agreed, Python is behind here. I'm not the best at data viz, but I can usually piece together a way to make ggplot do what I want it to do without that much trouble or looking at documentation. Matplotlib, though ... that's a harder beast to internalize. I know it's possible to make high-quality matplotlib plots, but it's much harder for me. Like pandas, it's a library that I don't want to denigrate because I know people put lots of effort into it, but I can't lie -- I'm not a fan.
- mindv0rtex 5y ago
  Speaking of what's possible in matplotlib, I am very much looking forward to reading this book: https://github.com/rougier/scientific-visualization-book https://github.com/rougier/scientific-visualization-book
RobinL 5y ago
I don't think it's correct to say Python is far behind in the viz space at all. It's just different. I primarily use Altair within Python. ggplot is ahead of Altair in some respects, but behind in others. For example, here is a chart which can be made in Altair: https://altair-viz.github.io/gallery/seattle_weather_interactive.html https://altair-viz.github.io/gallery/seattle_weather_interac... Note: - You can brush over the date range to filter the bar chart - You can click on weather type to filter the scatter chart - It can be embedded in any webpage with these interactive elements in tact. Since the chart is represented by json and rendered by javascript, the spec also embeds the data within the chart itself, and allows the user to therefore change the chart however they want You can even build something like gapminder: https://vega.github.io/vega-lite/examples/interactive_global_development.html https://vega.github.io/vega-lite/examples/interactive_global... More examples here: https://altair-viz.github.io/gallery/ https://altair-viz.github.io/gallery/
abacadaba 5y ago
Ah SAS, the one language that makes R look good.

mrtranscendence 5y ago

There are Python ports of ggplot (e.g. plotnine (https://github.com/has2k1/plotnine https://github.com/has2k1/plotnine)), but agreed, Python is behind here. I'm not the best at data viz, but I can usually piece together a way to make ggplot do what I want it to do without that much trouble or looking at documentation. Matplotlib, though ... that's a harder beast to internalize. I know it's possible to make high-quality matplotlib plots, but it's much harder for me. Like pandas, it's a library that I don't want to denigrate because I know people put lots of effort into it, but I can't lie -- I'm not a fan.

mindv0rtex 5y ago
Speaking of what's possible in matplotlib, I am very much looking forward to reading this book: https://github.com/rougier/scientific-visualization-book https://github.com/rougier/scientific-visualization-book

RobinL 5y ago

I don't think it's correct to say Python is far behind in the viz space at all. It's just different. I primarily use Altair within Python. ggplot is ahead of Altair in some respects, but behind in others. For example, here is a chart which can be made in Altair: https://altair-viz.github.io/gallery/seattle_weather_interactive.html https://altair-viz.github.io/gallery/seattle_weather_interac... Note: - You can brush over the date range to filter the bar chart - You can click on weather type to filter the scatter chart - It can be embedded in any webpage with these interactive elements in tact. Since the chart is represented by json and rendered by javascript, the spec also embeds the data within the chart itself, and allows the user to therefore change the chart however they want You can even build something like gapminder: https://vega.github.io/vega-lite/examples/interactive_global_development.html https://vega.github.io/vega-lite/examples/interactive_global... More examples here: https://altair-viz.github.io/gallery/ https://altair-viz.github.io/gallery/

abacadaba 5y ago

Ah SAS, the one language that makes R look good.