One of my favorite statistics teachers once told the class. Computers process information sequentially, but humans see things holographically. We have a whole set of sensors and wirings that can compute fast and make the right call. We are after all the survivors of evolution. Visualization is powerful in utilizing our innate ability to see things fast.
The density, spread and skewdness of a variable. Multiple variables can be placed side by side or stacked or overlapped.
The interaction, collinearity and even causation between two variables.
script
package
plot
R
wordcloud
wordcloud()
script
package
plot
R
ggplot2
geom_col()
script
package
plot
R
ggplot2
geom_boxplot()
script
package
plot
Python
seaborn
distplot()
script
package
plot
R
ggplo2
geom_line()
script
package
plot
Python
seaborn
kdeplot()
script
package
plot
R
ggplot2
grid.arrange()
script
package
plot
R
stats
lines(density())
script
package
plot
Python
matplotlib
plot(kind='bar')
script
package
plot
R
car
symbox()
script
package
plot
R
ggplot2
geom_line()
script
package
plot
R
effects
plot(alleEffects())
script
package
plot
R
stats
interaction.plot()
script
package
plot
R
cobalt
love.plot()
script
package
plot
R
PerformanceAnalytics
chart.Correlation()
script
package
plot
R
sensemakr
plot(sensemakr())
script
package
plot
Python
matplotlib
plot(kind='scatter')
script
package
plot
R
graphics
contour()
script
package
plot
R
ggplot2
geom_smooth()
script
package
plot
R
ggplot2
geom_point()