23.1 Providing the appropriate amount of context.20.1 Designing legends with redundant coding.19.3 Not designing for color-vision deficiency.19.2 Using non-monotonic color scales to encode data values.19.1 Encoding too much or irrelevant information.18.1 Partial transparency and jittering.
17.2 Visualizations along logarithmic axes.16.3 Visualizing the uncertainty of curve fits.16.2 Visualizing the uncertainty of point estimates.16.1 Framing probabilities as frequencies.14.3 Detrending and time-series decomposition.14.2 Showing trends with a defined functional form.13.3 Time series of two or more response variables.13.2 Multiple time series and dose–response curves.13 Visualizing time series and other functions of an independent variable.12 Visualizing associations among two or more quantitative variables.10.4 Visualizing proportions separately as parts of the total.10.3 A case for stacked bars and stacked densities.9.2 Visualizing distributions along the horizontal axis.9.1 Visualizing distributions along the vertical axis.9 Visualizing many distributions at once.8.1 Empirical cumulative distribution functions.8 Visualizing distributions: Empirical cumulative distribution functions and q-q plots.7.2 Visualizing multiple distributions at the same time.7 Visualizing distributions: Histograms and density plots.3.3 Coordinate systems with curved axes.2.2 Scales map data values onto aesthetics.2 Visualizing data: Mapping data onto aesthetics.
#Visualize value of stock software
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