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It's useful to have a diverging color palette for data visualization, such as stock returns, with negative values in red, zero in white, and positive values in green.
Currently, one can set the maximum and minimum values for the color domain, but when the range of values is asymmetrical, zero will not map to white. This can lead to a misleading representation as zero may not visually appear as a neutral midpoint.
A common workaround is to manually set symmetric bounds like [-values.abs().max(), values.abs().max()], but this can under-represent the intensity at one of the extremes since cell colors may not reach the full intensity of the designated color.
An effective solution would be to introduce a color midpoint option in the data_color() settings. This could ensure zero (in my example) is always represented by white and both extremes achieve full color intensity.
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It's useful to have a diverging color palette for data visualization, such as stock returns, with negative values in red, zero in white, and positive values in green.
Currently, one can set the maximum and minimum values for the color domain, but when the range of values is asymmetrical, zero will not map to white. This can lead to a misleading representation as zero may not visually appear as a neutral midpoint.
A common workaround is to manually set symmetric bounds like
[-values.abs().max(), values.abs().max()]
, but this can under-represent the intensity at one of the extremes since cell colors may not reach the full intensity of the designated color.An effective solution would be to introduce a color midpoint option in the
data_color()
settings. This could ensure zero (in my example) is always represented by white and both extremes achieve full color intensity.Beta Was this translation helpful? Give feedback.
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