How to plot a boxplot using aggregates in plotly?

Question

I need to plot a series of boxplots, based on results of numerical air quality model. Since this is a significant amount of data, I trigger calculation of aggregates (min, max, quartiles, etc.) every time when new model results become ready and store them in PostgreSQL. For visualization purpose I load the aggregates into pandas and I plot them using dash. I am able to plot line plots of timeseries, however I would like to get something like this example, but also interactive.

As I went through plotly examples, it looks like it always require the raw data for ploting boxplots ( https://plot.ly/python/box-plots/#basic-box-plot ). I really enjoy the concept of presentation and logic separation. Is it possible to get a plotly box plot based on aggregated data?

this work with Javascript but should probably work with Python as well: stackoverflow.com/questions/53944430/… — Maximilian Peters
– Maximilian Peters, Commented Jan 10, 2019 at 19:24

Maximilian Peters · Accepted Answer · 2019-01-18 17:09:15Z

5

You can provide your aggreate values to a Plotly boxplot in Python by providing it in the following format:

plotly.graph_objs.Box(y=[val_min, 
                         val_lower_box, 
                         val_lower_box, 
                         val_median, 
                         val_upper_box, 
                         val_upper_box, 
                         val_max])

e.g.

import plotly
plotly.offline.init_notebook_mode()

val_min = 1
val_lower_box = 2
val_median = 3
val_upper_box = 4.5
val_max = 6

box_plot = plotly.graph_objs.Box(y=[val_min, 
                                    val_lower_box, 
                                    val_lower_box, 
                                    val_median, 
                                    val_upper_box, 
                                    val_upper_box, 
                                    val_max])
plotly.offline.iplot([box_plot])

gives you

edited Jan 18, 2019 at 17:09

answered Jan 12, 2019 at 13:05

Maximilian Peters

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1 Comment

Marcin Kawka Over a year ago

Thank you Maximillian. That's a smart walkaround.

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