I feel you :)

Actually yes!

1. For "continuous color scales": (2. For discrete color scales)

2. For discrete color scales:

(Have fun ;))

Here is a full list of named colors:

https://www.w3.org/TR/css-color-3/#svg-color

Thanks for the info, but I have yet another question. How would I convert to rgb a color like “green” programmatically? · I understand I can go get the above mentioned link and extract it from there but is there any functionality in plotly to do so? · For example this px.colors.convert_colors_to_same_type(['red', 'blue', (0, 0.5, 1)], ) · returns: ([‘red’, ‘blue’, ‘rgb(0, 128, 255)’], None) · Which I don’t think is the intended output · I"m looking for something like px.colors.to_rgb(“reed”) → ‘rgb(255, 0, 0)’ · Thanks for reading

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() · image1879×507 22.6 KB