Hello! I am trying to add a wheel zoom tool to my bokeh boxplot, but for some reason I can’t get the range to be constrained. I’m using the bokeh documentation with the cars as an example:
p.x_range = FactorRange(factors = kinds, bounds = 'auto')
wheel_zoom = WheelZoomTool(maintain_focus=False)
pan = PanTool()
p.add_tools(wheel_zoom, pan)
p.toolbar.active_scroll = wheel_zoom
p.toolbar.active_drag = pan
p.add_tools(ResetTool())
Even though I’ve set the bounds to be automatically assigned according to the labels, I am still able to zoom out beyond the range of the categorical axis. Is there something I can do to constrain the range of the x-axis between the first label and the last label when using Wheel Zoom? Thanks!
Here is the complete code for reproducibility
import pandas as pd
from bokeh.models import ColumnDataSource, Whisker, WheelZoomTool, ResetTool, PanTool, FactorRange
from bokeh.plotting import figure, show
from bokeh.sampledata.autompg2 import autompg2
from bokeh.transform import factor_cmap
df = autompg2[["class", "hwy"]].rename(columns={"class": "kind"})
kinds = df.kind.unique()
# compute quantiles
grouper = df.groupby("kind")
qs = grouper.hwy.quantile([0.25, 0.5, 0.75]).unstack().reset_index()
qs.columns = ["kind", "q1", "q2", "q3"]
# compute IQR outlier bounds
iqr = qs.q3 - qs.q1
qs["upper"] = qs.q3 + 1.5*iqr
qs["lower"] = qs.q1 - 1.5*iqr
# update the whiskers to actual data points
for kind, group in grouper:
qs_idx = qs.query(f"kind=={kind!r}").index[0]
data = group["hwy"]
# the upper whisker is the maximum between p3 and upper
q3 = qs.loc[qs_idx, "q3"]
upper = qs.loc[qs_idx, "upper"]
wiskhi = group[(q3 <= data) & (data <= upper)]["hwy"]
qs.loc[qs_idx, "upper"] = q3 if len(wiskhi) == 0 else wiskhi.max()
# the lower whisker is the minimum between q1 and lower
q1 = qs.loc[qs_idx, "q1"]
lower = qs.loc[qs_idx, "lower"]
wisklo = group[(lower <= data) & (data<= q1)]["hwy"]
qs.loc[qs_idx, "lower"] = q1 if len(wisklo) == 0 else wisklo.min()
df = pd.merge(df, qs, on="kind", how="left")
source = ColumnDataSource(qs)
p = figure(x_range=kinds, tools="", toolbar_location=None,
title="Highway MPG distribution by vehicle class",
background_fill_color="#eaefef", y_axis_label="MPG")
# outlier range
whisker = Whisker(base="kind", upper="upper", lower="lower", source=source)
whisker.upper_head.size = whisker.lower_head.size = 20
p.add_layout(whisker)
# quantile boxes
cmap = factor_cmap("kind", "TolRainbow7", kinds)
p.vbar("kind", 0.7, "q2", "q3", source=source, color=cmap, line_color="black")
p.vbar("kind", 0.7, "q1", "q2", source=source, color=cmap, line_color="black")
# outliers
outliers = df[~df.hwy.between(df.lower, df.upper)]
p.scatter("kind", "hwy", source=outliers, size=6, color="black", alpha=0.3)
p.xgrid.grid_line_color = None
p.axis.major_label_text_font_size="14px"
p.axis.axis_label_text_font_size="12px"
p.toolbar_location = None
p.x_range = FactorRange(factors = kinds, bounds = 'auto')
wheel_zoom = WheelZoomTool(maintain_focus=False)
pan = PanTool()
p.add_tools(wheel_zoom, pan)
p.toolbar.active_scroll = wheel_zoom
p.toolbar.active_drag = pan
p.add_tools(ResetTool())
show(p)
