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This is a graph that I got from Minitab that I would like to replicate this on Seaborn for better quality.

Boxplot from Minitab

enter image description here

My data looks like this:

enter image description here

I tried using a FacetGrid and then mapping with sns.boxplot but that wasn't working. Should I try to use groupby on the Layer thickness instead? I am a beginner in data viz using python and any help on this would be great.

sbgib
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Kaushik Venkatesh
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    Please don't show data as images. check out [How to make good reproducible pandas examples](https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples) . This looks like a simple boxplot with `hue` nesting. refer to [the 3rd example here](https://seaborn.pydata.org/generated/seaborn.boxplot.html?highlight=boxplot#seaborn.boxplot). Try to implement that, and come back if you encounter a *specific* problem with the implementation. – Diziet Asahi Dec 03 '20 at 08:36
  • @DizietAsahi Can I rewrite the question ,with an example ,as a new one or should I edit it out completely – Kaushik Venkatesh Dec 03 '20 at 13:15
  • @KaushikVenkatesh If you don't wait too long, you can edit the question with toy data and the code you tried. (If too much time passes, the question might get buried into the pile of old questions. In that case, it might be better to ask a new question, updated with your new insights.) – JohanC Dec 03 '20 at 14:02
  • I figured how to do it :). – Kaushik Venkatesh Dec 03 '20 at 15:23
  • I just melted the dataframe like so – Kaushik Venkatesh Dec 03 '20 at 15:23
  • `melted= pd.melt(Radata, id_vars=['PRINTING SPEED','EXTRUDER TEMP', 'LAYER THICKNESS'], value_vars=['RA TOP ','RA BOTTOM ','RA SIDE 1', 'Ra round', 'ra slant'])` and then called the graph like so `sns.boxplot(x= "variable", y = 'value', hue= 'LAYER THICKNESS', data= melted)` . Hope this method is fine, or is there an easier way to do it? Thank You for your help @DizietAsahi and @JohanC – Kaushik Venkatesh Dec 03 '20 at 15:25
  • Sorry for the multiple comments.. I am new User here – Kaushik Venkatesh Dec 03 '20 at 15:25

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