Thanks for the list of available colours above.
I made a simple table based on the list to quickly see what the colours look like:
def show_named_plotly_colours():
"""
function to display to user the colours to match plotly's named
css colours.
Reference:
#https://community.plotly.com/t/plotly-colours-list/11730/3
Returns:
plotly dataframe with cell colour to match named colour name
"""
s='''
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, saddlebrown, salmon, sandybrown,
seagreen, seashell, sienna, silver, skyblue,
slateblue, slategray, slategrey, snow, springgreen,
steelblue, tan, teal, thistle, tomato, turquoise,
violet, wheat, white, whitesmoke, yellow,
yellowgreen
'''
li=s.split(',')
li=[l.replace('\n','') for l in li]
li=[l.replace(' ','') for l in li]
import pandas as pd
import plotly.graph_objects as go
df=pd.DataFrame.from_dict({'colour': li})
fig = go.Figure(data=[go.Table(
header=dict(
values=["Plotly Named CSS colours"],
line_color='black', fill_color='white',
align='center', font=dict(color='black', size=14)
),
cells=dict(
values=[df.colour],
line_color=[df.colour], fill_color=[df.colour],
align='center', font=dict(color='black', size=11)
))
])
fig.show()
