This is python code written on jupyter notebook. which produces the following gr

Question

This is python code written on jupyter notebook.

which produces the following graph.

Can the the points on the graph be connected with a line, all the blue points connected to each other and then all the red points connected to each other.

Can error be added nto the plot, can it be shaded like it is in the following plot. can the value for the error be 1.5.

# Create a blank figure with labels
p = figure(plot_width = 600, plot_height = 600,
title = 'Average Number of Units Lost per Engagement',
x_axis_label = 'X', y_axis_label = 'Y')

# Example data
squares_x = [1.295, 2.068, 2.915, 4.203, 5.05, 6.08, 6.891, 7.702, 8.07, 9.984]
squares_y = [0.0005627, 0.0377, 1.003, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01]
circles_x = [9, 12, 4, 3, 15]
circles_y = [8, 4, 11, 6, 10]

# Add squares glyph
p.square(squares_x, squares_y, size = 12, color = 'navy', alpha = 0.6)
# Add circle glyph
p.circle(circles_x, circles_y, size = 12, color = 'red')

# Set to output the plot in the notebook
output_notebook()
# Show the plot
show(p)

2 from bokeh.plotting import figure 3 from bokeh.io import show, output_notebook 5 # Create a blank figure with labels 6 p-figure(plot width- 600, plot_height600, title-'Average Number of Units Lost per Engagement', x axis label "?, y axis label ) 10 # Example data 11 squaresx[1.295, 2.068, 2.915, 4.03, 5.05, 6.08, 6.891, 7.702, 8.07, 9.984] 12 squares-y= [0.0005627, ?·0377, 1.0?3, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] 13 circles_x[9, 12, 4, 3, 15] 14 circles y [8, 4, 11, 6, 10] 15 16 # Add squares glyph 17 ?.square ( squares-x, squares-y , size- 12, color- 'navy, alpha-0.6) 18 # Add circle glyph 19 p.circle(circles_x, circles_y, size-12, color'red') 20 21 # Set to output the plot in the notebook 22 output_notebok) 23 # Show the plot 24 show(p) 25 2 2 8 2 3

Explanation / Answer

SOLUTION:

The band thing can be done using patch of bookeh. Although, since the circles data is not sorted in x axis, the code gives a little unexpected filling in overlapping areas of plot. I advise you to sort your data according to x-axis data points and then it will give you a better plot. (Although, if data is collected in that order and needs to be strictly in that order than keep it as it is).

CODE:

import numpy as np

from bokeh.plotting import figure

from bokeh.io import show, output_notebook

# Create a blank figure with labels

p = figure(plot_width = 600, plot_height = 600,

title = 'Average Number of Units Lost per Engagement',

x_axis_label = 'X', y_axis_label = 'Y')

# Example data

squares_x = [1.295, 2.068, 2.915, 4.203, 5.05, 6.08, 6.891, 7.702, 8.07, 9.984]

squares_y = [0.0005627, 0.0377, 1.003, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01]

circles_x = [9, 12, 4, 3, 15]

circles_y = [8, 4, 11, 6, 10]

# Add squares glyph

p.square(squares_x, squares_y, size = 12, color = 'navy', alpha = 0.6)

# Add circle glyph

p.circle(circles_x, circles_y, size = 12, color = 'red')

# Add lines connecting both datapoints

p.line(squares_x, squares_y, line_width = 2, color = 'navy')

p.line(circles_x, circles_y, line_width = 2, color = 'red')

# Error Band for Square line

# Define Error Bands for square line

upperband = [k+1.5 for k in squares_y] #can change error value here, currently put 1.5 as requested in question

lowerband = [k-1.5 for k in squares_y] #can change error value here, currently put 1.5 as requested in question

# Error shading glyph:

band_x = np.append(squares_x, squares_x[::-1])

band_y = np.append(lowerband, upperband[::-1])

p.patch(band_x, band_y, color='navy', fill_alpha=0.2)

# Error Band for Circle line

# Define Error Bands for circle line

upperband = [k+1.5 for k in circles_y] #can change error value here, currently put 1.5 as requested in question

lowerband = [k-1.5 for k in circles_y] #can change error value here, currently put 1.5 as requested in question

# Error shading glyph:

band_x = np.append(circles_x, circles_x[::-1])

band_y = np.append(lowerband, upperband[::-1])

p.patch(band_x, band_y, color='red', fill_alpha=0.2)

# Set to output the plot in the notebook

output_notebook()

# Show the plot

show(p)

Also, if you do not want the error band to have boundaries as with above bookeh code, you may give a try to matplotlib. A brief example to use it for your squares data is below:

import numpy as np
import matplotlib.pyplot as plt

def errorfill(x, y, yerr, color=None, alpha_fill=0.2):
ax = plt.gca()
if color is None:
color = 'navy'
if np.isscalar(yerr) or len(yerr) == len(y):
ymin = [x-yerr for x in y]
ymax = [x+yerr for x in y]
elif len(yerr) == 2:
ymin, ymax = yerr
ax.plot(x, y, color=color)
ax.fill_between(x, ymax, ymin, color=color, alpha=alpha_fill)

squares_x = [1.295, 2.068, 2.915, 4.203, 5.05, 6.08, 6.891, 7.702, 8.07, 9.984]
squares_y = [0.0005627, 0.0377, 1.003, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01]

errorfill(squares_x , squares_y, 1.5)

plt.show()

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