band

An interactive numerical band plot based on simple Python array of data.

It is a combination of scatter plots and line plots added with a band of covered area. The line passes through the mean of the area covered by the band.

Details

Bokeh APIs:

bokeh.models.Band, bokeh.models.ColumnDataSource, bokeh.plotting.figure, bokeh.io.show

More info:

Bands

Keywords:

figure, scatter, line, band, layout

import numpy as np
import pandas as pd

from bokeh.models import Band, ColumnDataSource
from bokeh.plotting import figure, show

# Create some random data
x = np.random.random(2500) * 140 +20
y = np.random.normal(size=2500) * 2 + 6 * np.log(x)

df = pd.DataFrame(data=dict(x=x, y=y)).sort_values(by="x")

df2 = df.y.rolling(window=300).agg({"y_mean": "mean", "y_std": "std"})

df = pd.concat([df, df2], axis=1)
df["lower"] = df.y_mean - df.y_std
df["upper"] = df.y_mean + df.y_std

source = ColumnDataSource(df.reset_index())

p = figure(tools="", toolbar_location=None, x_range=(40, 160))
p.title.text = "Rolling Standard Deviation"
p.xgrid.grid_line_color=None
p.ygrid.grid_line_alpha=0.5

p.scatter(x="x", y="y", color="blue", marker="dot", size=10, alpha=0.4, source=source)

p.line("x", "y_mean", line_dash=(10, 7), line_width=2, source=source)

band = Band(base="x", lower="lower", upper="upper", source=source,
            fill_alpha=0.3, fill_color="yellow", line_color="black")
p.add_layout(band)

show(p)