

In [1]:

    
from ggplot import *
%matplotlib inline

Aesthetics

Aesthetics describe how your data will relate to your plots. Some common aesthetics are: x, y, and color. Aesthetics are specific to the type of plot (or layer) you're adding to your visual. For example, a scatterplot (geom_point) and a line (geom_line) will share x and y, but only a line chart has a linetype aesthetic.

Aesthetics are specific to geoms, but here is a list of all of them:

x : x-axis value. Can be used for continuous (point, line) charts and for discrete (bar, histogram) charts.
y : y-axis value. Can be used for continuous charts only
color : color of a layer. Can be continuous or discrete. If continuous, this will be given a color gradient between 2 colors.
shape : shape of a point. Can be used only with geom_point
size : size of a point or line. Used to give a relative size for a continuous value
alpha : transparency level of a point. Number between 0 and 1. Only supported for hard coded values.
ymin : min value for a vertical line or a range of points. See geom_area, geom_ribbon, geom_vline
ymax : max value for a vertical line or a range of points. See geom_area, geom_ribbon, geom_vline
xmin : min value for a horizonal line. Specific to geom_hline
xmax : max value for a horizonal line. Specific to geom_hline
slope : slope of an abline. Specific to geom_abline
intercept : intercept of an abline. Specific to geom_abline



In [2]:

    
# set the x-axis equal to the `date` column and the y-axis equal to the `beef` column
my_aes = aes(x='date', y='beef')
my_aes









    Out[2]:





{'y': 'beef', 'x': 'date'}



In [3]:

    
ggplot(meat, my_aes) + geom_line()









    












    Out[3]:





<ggplot: (288207577)>



In [4]:

    
# normally, aes are defined within the `ggplot` constructor
ggplot(aes(x='carat', y='price'), diamonds) + geom_point()









    












    Out[4]:





<ggplot: (288335565)>



In [5]:

    
# adding in another aesthetic into the mix...
ggplot(aes(x='carat', y='price', color='clarity'), diamonds) + geom_point()









    












    Out[5]:





<ggplot: (288823329)>



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