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If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] & 

If you want to remove colors from 2D bins use `ColorFunction -> (White &) to get:

Note: I used a custom ChartElementFunction to add the data points above. Alternatively, you can replace the option ChartElementFunction -> ... with

Epilog -> {First[ListPlot[data, PlotStyle -> Directive[Black, AbsolutePointSize @ 3]]]} 

to get the same picture.

If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] 

If you want to remove colors from 2D bins use `ColorFunction -> (White &) to get:

Note: I used a custom ChartElementFunction to add the data points above. Alternatively, you can replace the option ChartElementFunction -> ... with

Epilog -> {First[ListPlot[data, PlotStyle -> Directive[Black, AbsolutePointSize @ 3]]]} 

to get the same picture.

If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] & 

If you want to remove colors from 3D bins use `ColorFunction -> (White &) to get:

Note: I used a custom ChartElementFunction to add the data points above. Alternatively, you can replace the option ChartElementFunction -> ... with

Epilog -> {First[ListPlot[data, PlotStyle -> Directive[Black, AbsolutePointSize @ 3]]]} 

to get the same picture.

If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] & 

If you want to remove colors from 2D bins use `ColorFunction -> (White &) to get:

Note: I used a custom ChartElementFunction to add the data points above. Alternatively, you can replace the option ChartElementFunction -> ... with

Epilog -> {First[ListPlot[data, PlotStyle -> Directive[Black, AbsolutePointSize @ 3]]]} 

to get the same picture.

If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] & 

If you don't mind having histograms on left and bottom frames you can use DensityHistogram with the Method suboption "DistributionAxes".

With this approach, in addition to histograms, you can have box-whisker chart, smooth histogram or data rug to represent the marginal distributions of input data:

SeedRandom[1] data = RandomReal[BinormalDistribution[{0, 0}, {1, 1}, 0.5], 300]; DensityHistogram[data, {15, 12}, ImageSize -> Medium, ColorFunction -> (Blend[{LightRed, Red}, #] &), Method -> {"DistributionAxes" -> #}, PlotLabel -> Style[#, 16], ChartElementFunction -> ({ChartElementData["Rectangle"][##], Black, AbsolutePointSize @ 3, Point @ #2} &)] & /@ {"Histogram", "Lines", "BoxWhisker", "SmoothHistogram"} Multicolumn[%, 2] & 

If you want to remove colors from 3D bins use `ColorFunction -> (White &) to get:

Note: I used a custom ChartElementFunction to add the data points above. Alternatively, you can replace the option ChartElementFunction -> ... with

Epilog -> {First[ListPlot[data, PlotStyle -> Directive[Black, AbsolutePointSize @ 3]]]} 

to get the same picture.