Rounding Numbers in a Quartile Figures of a Plotly Box Plot

Question

I have been digging around a while trying to figure out how to round the numbers displayed in quartile figures displayed in the hover feature. There must be a straightforward to do this as it is with the x and y coordinates. In this case rounding to two decimals would be sufficient.

df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/tips.csv")

fig = go.Figure(data=go.Box(y=df['total_bill'],
                            name='total_bill',
                            boxmean=True,
                           )
               )

fig.update_layout(width=800, height=800,
                  hoverlabel=dict(bgcolor="white",
                                  font_size=16,
                                  font_family="Arial",
                                 )
                 )
fig.show()

Answer 1

Unfortunately this is something that it looks like Plotly cannot easily do. If you modify the hovertemplate, it will only apply to markers that you hover over (the outliers), and the decimals after each of the boxplot statistics will remain unchanged upon hovering. Another issue with plotly-python is that you cannot extract the boxplot statistics because this would require you to interact with the javascript under the hood.

However, you can calculate the boxplot statistics on your own using the same method as plotly and round all of the statistics down to two decimal places. Then you can pass boxplot statistics: lowerfence, q1, median, mean, q3, upperfence to force plotly to construct the boxplot manually, and plot all the outliers as another trace of scatters.

This is a pretty ugly hack because you are essentially redoing all of calculations Plotly already does, and then constructing the boxplot manually, but it does force the boxplot statistics to display to two decimal places.

from math import floor, ceil
from numpy import mean
import pandas as pd
import plotly.graph_objects as go

df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/tips.csv")

## calculate quartiles as outlined in the plotly documentation 
def get_percentile(data, p):
    data.sort()
    n = len(data)
    x = n*p + 0.5
    x1, x2 = floor(x), ceil(x)
    y1, y2 = data[x1-1], data[x2-1] # account for zero-indexing
    return round(y1 + ((x - x1) / (x2 - x1))*(y2 - y1), 2)

## calculate all boxplot statistics
y = df['total_bill'].values
lowerfence = min(y)
q1, median, q3 = get_percentile(y, 0.25), get_percentile(y, 0.50), get_percentile(y, 0.75)
upperfence = max([y0 for y0 in y if y0 < (q3 + 1.5*(q3-q1))])

## construct the boxplot
fig = go.Figure(data=go.Box(
    x=["total_bill"]*len(y),
    q1=[q1], median=[median], mean=[round(mean(y),2)],
    q3=[q3], lowerfence=[lowerfence],
    upperfence=[upperfence], orientation='v', showlegend=False,
    )
)

outliers = y[y>upperfence]
fig.add_trace(go.Scatter(x=["total_bill"]*len(outliers), y=outliers, showlegend=False, mode='markers', marker={'color':'#1f77b4'}))
               

fig.update_layout(width=800, height=800,
                  hoverlabel=dict(bgcolor="white",
                                  font_size=16,
                                  font_family="Arial",
                                 )
                 )

fig.show()