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In the new symbology mode, at least in 1.8.0, several classification modes render negative real values as though they were positive values. This occurs with Quantile, Natural Breaks and Standard Deviation classifications. It also fails completely to classify percentages stored as reals (-1 to 1) in Equal Interval and Pretty Breaks modes.

I have import data (from either CSV or XLS) and join it to a vector layer. The data is attached, although with identifying information stripped out because it's embargoed.

The values range from -0.0791 to 0.0165 and are stored as reals. The classifications are a mess; for instance, here's the classification in Quantile mode, in order from lightest color to darkest for 7 categories:

0.0000 - -0.0342
-0.0342 - -0.0185
-0.0185 - 0.0000
0.0000 - 0.0000
0.0000 - 0.0000
0.0000 - 0.0000
0.0000 - 0.0165

I don't know why it includes three categories of 0-0, but it leads to misleading categorization. The data has a MIN of -0.0791 so it should be something like

-0.0791 - -0.0345
-0.0342 - -0.0185
-0.0185 - 0.0000
0.0000 - 0.0165

off the top of my head, although of course that's only 4 categories. There are 56 data points, so it's not for lack of trying.