I have a Pandas DataFrame, luminance_df, that looks like this:

	barelyvisible	ultralight	light	abitlight	medium	abitdark	dark	evendarker	ultradark	almostblack
orange	96	92	83	72	61	53	48	40	34	28
gold	96	89	77	65	56	50	44	37	31	26
yellow	95	88	77	64	53	47	40	33	29	26
chartreuse	95	89	80	67	55	44	35	27	23	20
green	97	93	85	73	58	45	36	29	24	20
forest	96	90	80	67	52	39	30	24	20	16
aqua	97	89	78	64	50	40	32	26	22	19
teal	96	90	82	69	53	43	36	31	27	24
lightblue	97	94	86	74	60	48	39	32	27	24
blue	97	93	87	78	68	60	53	48	40	33
indigo	97	94	89	82	74	67	59	51	41	34
purple	98	95	92	85	76	66	58	50	42	35
royalpurple	98	95	92	85	75	65	56	47	39	32
magenta	98	95	91	83	73	61	49	40	33	28
pink	97	95	90	82	70	60	51	42	35	30
dustypink	97	95	90	82	71	60	50	41	35	30
red	97	94	89	82	71	60	51	42	35	31

So far, I'm building a single multi-chart HTML file like this:

with open(os.path.join(cwd, 'testout.html'), 'w') as outfile:
    outfile.write("<p>&nbsp;</p><hr/><p>&nbsp;</p>".join(['<h1>Colors</h1>' hex_styler.to_html(), '<h1>Hue</h1>' hue_styler.to_html(), '<h1>Saturation</h1>' saturation_styler.to_html(
    ), '<h1>Luminance</h1>' luminance_styler.to_html(), '<h1>Perceived Brightness</h1>' perceived_brightness_pivot_styler.to_html(), '<h1>Base Data</h1>' basic_df.to_html()]))

I'd like to display an elevation/contour style map of the Luminance right after luminance_styler.to_html(), a lot like this one that I produced in Excel:

I'd like the colors to stay sorted "top to bottom" as values on a y-axis and the darknesses to stay sorted "left to right" as values on an x-axis, just like in the example above.

Question

I'm not a data scientist, nor do I use Python terribly regularly. I'm proud of myself for having made luminance_df in the first place, but I am not, for the life of me, figuring out how to make Python simply ... treat numeric cell values in a DataFrame whose labels in both directions are strings ... as a z-axis and make a contour-chart of it.

Everything I Google leads to really complicated data science nuanced questions.

Could someone get me on the right track by giving me the basic "hello world" code to get at least as far with luminance_df's data in Python as I got with the "insert chart" button in Excel?

If you can get me so I've got a img = BytesIO() that's image_base64 = base64.b64encode(img.read()).decode("utf-8")-able, I can f'<img src="data:image/png;base64, {image_base64}" />' it myself into the string concatenation that makes testout.html.

I'm on Windows and have myself set up to be able to pip install.

Notes

To be fair, I find these contour charts much more attractive and much easier to read than the one Excel made, but I'm fine with something sort of "brutish"-looking like the Excel version, as long as it makes "rising" & "falling" obvious and as long as it uses a ROYIGBV rainbow to indicate "less" vs. "more" (pet peeve of mine about the default Excel colors -- yes, I know, it's probably an accessibility thing):
While I'd like my chart's colors to follow a "rainbow" of sorts (because personally I find them easy to read), any "rainbow shading" on the chart should completely ignore the fact that the labels of the y-axis happen to describe colors. No correlation whatsoever. I'm simply plotting number facts between 16 and 98; colors of the chart should just indicate the change in "elevation" between those two extremes.

Effort so far

The only other "simple" question I've found so far that seems similar is

Or a heatmap:

import seaborn as sns
sns.heatmap(df, cmap='RdYlBu')

Output: