In this example, we want to scale up the x-axis by a factor of 60 to convert from minutes to seconds. This can create format objects for the axis tick marks The matplotlib.ticker library to provide access to the FuncFormatter() function.The t_major_formatter() or t_major_formatter() method, depending on which axis you want to change the format of.If you want to change the scale on an axis (eg show the tick marks in units of seconds when your data is in minutes) you can edit its format using the following: Y_4 = Īx.scatter(x_1, y_1, label='First data set')Īx.scatter(x_2, y_2, label='Second data set')Īx.scatter(x_3, y_3, label='Third data set')Īx.scatter(x_4, y_4, label='Fourth data set') This is created via ax.legend() after having specified the label keyword argument in the ax.scatter() calls: x_1 = When doing this, it’s usually best to include a legend. To plot multiple data series on the same axes, simply use the ax.scatter() function multiple times. To make this easier, it can be helpful to get the current limits of the axes using ax.get_ylim() and ax.get_xlim():Īx.set_title("Anscombe's First Data Set")Īx.set_facecolor((232 / 255, 232 / 255, 232 / 256)) Alter the aspect ratio of the plotting area using ax.set_aspect().Add text labels with ax.text(), specifying the x- and y-coordinates of the label along with the string that will appear there (read the full documentation for text labels here).This can be done in a for loop and is demonstrated in the example below. set_color() method of the spines (Matplotlib’s word for the axis lines). To colour the axis lines (eg if you want them to match your gridlines) you will need to use the.Use ax.set_axisbelow(True) after adding gridlines to move them behind your data points.If you want minor gridlines and axis ticks you will also need to use plt.minorticks_on().Gridlines: use the plt.grid() function in which you can set which gridlines to mark (major, minor or both) and the axis to apply the lines to (x, y or both), along with other keyword arguments related to line plots.Colour of the graph area: use the ax.set_facecolor((R, G, B)) function where R, G and B are the red, green and blue colour proportions on a scale of 0 to 1.Transparency of the markers: use the alpha keyword argument within plt.scatter().Some more options that can be tinkered with:
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