annotate ( 'Labor Day', xy = ( '', 4850 ), xycoords = 'data', ha = 'center', xytext = ( 0, - 20 ), textcoords = 'offset points' ) ax. annotate ( 'Independence Day', xy = ( '', 4250 ), xycoords = 'data', bbox = dict ( boxstyle = 'round', fc = 'none', ec = 'gray' ), xytext = ( 10, - 40 ), textcoords = 'offset points', ha = 'center', arrowprops = dict ( arrowstyle = '->' )) ax. annotate ( 'New Year's Day', xy = ( '', 4100 ), xycoords = 'data', xytext = ( 50, - 30 ), textcoords = 'offset points', arrowprops = dict ( arrowstyle = '->', connectionstyle = 'arc3,rad=-0.2' )) ax. plot ( ax = ax ) # Add labels to the plot ax. subplots ( figsize = ( 12, 4 )) births_by_date. Here let's look at an example of drawing text at various locations using these transforms:įig, ax = plt. fig.transFigure: Transform associated with the figure (in units of figure dimensions).ax.transAxes: Transform associated with the axes (in units of axes dimensions).ax.transData: Transform associated with data coordinates.There are three pre-defined transforms that can be useful in this situation: The average user rarely needs to worry about the details of these transforms, but it is helpful knowledge to have when considering the placement of text on a figure.

Mathematically, such coordinate transformations are relatively straightforward, and Matplotlib has a well-developed set of tools that it uses internally to perform them (these tools can be explored in the ansforms submodule). In Matplotlib, this is done by modifying the transform.Īny graphics display framework needs some scheme for translating between coordinate systems.įor example, a data point at $(x, y) = (1, 1)$ needs to somehow be represented at a certain location on the figure, which in turn needs to be represented in pixels on the screen. Sometimes it's preferable to anchor the text to a position on the axes or figure, independent of the data. In the previous example, we have anchored our text annotations to data locations. set ( title = 'USA births by day of year (1969-1988)', ylabel = 'average daily births' ) # Format the x axis with centered month labels ax. text ( '', 3850, 'Christmas ', ha = 'right', ** style ) # Label the axes ax. text ( '', 4250, 'Independence Day', ha = 'center', ** style ) ax. plot ( ax = ax ) # Add labels to the plot style = dict ( size = 10, color = 'gray' ) ax.

Matplotlib annotate center text