I am currently working on a map plot that has a wide range (0 - 5000) across different data sets. I need to have the colorbar to first be discrete, and show the full range even though in current dataset the max value may not be 5000, it might be 40. I have been following these three links
And was able to get the discrete colorbar. But my problem now is because of the such wide range of values, I need to somehow create the colorbar that has unequal bin size. So the colorbar might be something like
But when I specify range_color to be [0, 4000], it automatically creates equal sized buckets and all of my plots are shown as the same color when the overall values in the current dataset is small. So is there a way to specify “if the value is within this range, plot this color?” Thanks in advance.
What I came up with is the following: bin values into “color clusters” and use these “color clusters” afterwards to assign a color via the chosen colorscale. Maybe it’s not the most elegant way to do it, but this might work for you.
import plotly.graph_objects as go
import plotly.express as px
import numpy as np
# define discrete colorscale
colorscale = px.colors.qualitative.Dark2
# custom colorscale
#colorscale = ['red', 'green', 'pink', 'blue', 'black']
# set ranges
ranges = [
[0, 10],
[11, 20],
[21, 50],
[51, 300],
[301, 1000]
]
# create dummy data
x = np.random.randint(0,50,500)
y = np.random.randint(0,999,500)
# bin values into color clusters
def bin_colors(value):
for color, r in enumerate(ranges):
if r[0] <= value <= r[1]:
return color
color_cluster = list(map(bin_colors, y))
# create figure
fig = go.Figure()
fig.add_scatter(
x=x,
y=y,
mode='markers',
marker={
'color': color_cluster,
'colorscale': colorscale
}
)
fig.update_yaxes(type="log")
