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- Data/Amounts -  - {:height 407, :width 854} - Horizontal Bars - Vertical Bards - Dots - Grouped Bars - Stacked Bards - Heatmap - - Data/Distributions - {:height 231, :width 952} - {:height 453, :width 950} - Histograms - Density Plot - Cumulative Density - Quantile-Quantile Plot - Boxplot - Violin - Strip Chart - Sina Plot - Stacked Histograms - Overlapping Densities - Ridgeline Plot - - Histograms and density plots most intuitive but require arbitrary parameter choices and can be misleading. - Cumulative densities and q-q faithful but difficult to interpret - - Data/Proportions -  -  -  - Stacked Bars awkward for single, but useful when comparing multiple sets of proportions - Stacked Density when proportions change over continuous variable - Mosaic, Treemaps or Parallel Sets when proportions are specified according to multiple groupings - Data/X-Y Relationships -  -  -  - Scatterplot - archetypical viz when showing one quantitative variable relative to another - Paired data (measured in same units) can be show as Slopegraph - Contour Lines, 2D Bins and Hex Bins - for large number of points - 3 variables? - we can map one onto dot size creating bubble plot. - More than 2 quantities - plot correlation coeff in the form of Correlogram - Line Graph - When x axis is time (or any strictly increasing quantity) - Use Smooth Line to represent trends in large dataset - Data/Geospatial Data -  - Primary way is in the form on Map. A 2D representation of globe approximating shape and distances - Choropleth - showing different regions in different colors - Cartogram - distort regions based on other quantity (eg: population) - Data/Uncertainity collapsed:: true -  -  -  - Error Bars - range of likely values - Graded Error Bars - different confidence can be show with thickness - Eyes and Half-Eyes - combine error bars with approaches to viz distribution (violins and ridgelines) - Confidence Band - Error Bar as Smooth Line Graph