Python Tutorial: Plotting multiple graphs

Key Takeaways

we've already seen that the pie plot module from matplotlib is our workhorse to construct plots quickly we'll see how to plot graphs on the same axes how to create additional tailored axes and how to create a grid of axes called subplots within a single figure to start let's assume we have three numpy raised t for time temperature and dew point these come from weather measurements over the course of two weeks in January 2010 the first plot command plots temperature versus T in red the arguments the plot can be numpy arrays lists or pandas series the curve is not actually drawn yet just created in memory the second plot command issued in sequence actually overlays a curve of dew point versus T in blue on the same axes the next two lines create a label for the horizontal axis and a title the last line with the show command actually displays the figure on screen once the sequence of plot objects from our prior instructions have been positioned this is the resulting figure with the two curves overlaid on the same axes notice the tick axis labels are messy here you'll see how to clean those up later common axes are convenient for comparing curves directly but they can get messy we'll try to draw the same two curves this time on multiple axes in the same figure overlaying curves is not useful when the scales differ wildly the tool to construct AXYZ explicitly is the axes command we'll explain the numbers shortly just realize that the axes command creates coordinate axes within a figure within which subsequent plots are drawn thus the first line constructs axes on the left side of the figure window and the subsequent three lines create a curve an axis label and a title within those axes the second axes command makes new axes on the right of the figure and also makes those axes active this means the next three commands place objects in the second axes not the first and again nothing is drawn until the show command the proceeding code snippet produces this figure the figures are laid out in separate axes with different vertical scales side-by-side the axes command requires the lower left corner the width and the height of the axes all expressed in Figure units by figure Units we mean numbers between zero and one scale to the dimensions of the figure getting those right sometimes requires some trial and error later you'll learn how to customize axes to draw an inset plot the subplot command creates a grid of axes freeing us from figuring out axis coordinates manually this figure has two rows and one column of axes created by subplot this vertical stacking of axes is slightly more pleasing than before this is the code that made the preceding figure the top subplot is active for the first four lines while the bottom subplot is active for the rest before showing the figure issuing tight layout pad spaces between the subplots so the tick labels and titles display without overlap the three subplot arguments are number of rows the number of columns and which subplot number to activate subplot numbers increase across rows and then down columns starting from number one in the top left corner notice subplot grids are indexed from one this is unlike other Python arrays again calling subplot with n rows in calls in subplot explicitly instructs where subsequent created plot objects go now it's your turn to practice making multiple plots