U, inv = np.unique(x1+x2, return_inverse=True)į = lambda c : plt.plot(,color=c, ls="", marker="o")Īx1. import matplotlib.pyplot as pltĬ = *len(x1) + *len(x2) Hence a solution which would also work for even lower versions would need to be used, plotting the values as numerical data. While matplotlib 2.1.0 allows in principle to plot categories, it is not possible to add further categories to an existing categorical axes. X1 = Īx1.scatter(x1, y1, color='black', label='Initial Fruits')Īx1.scatter(x2, y2, color='green', label='Further Fruits') From an Axes instance, you can plot your data using the ot and Axes.scatter methods, very similar to what you did through the pyplot interface. The code from the question runs fine in matplotlib 2.1.1 or higher. This is the suggested way to use matplotlib, especially when you need more customisation like in your case. See Chris's response above for a link to. There are some issues which are still being worked on. from matplotlib.patches import Ellipse plt.figure () ax plt.gca () ellipse Ellipse (xy (157.18, 68.4705), width0.036, height0.012, edgecolor'r', fc'None', lw2) ax.addpatch (ellipse) This code is based partially on the very first code box on this page. Scatter plots where one axis is categorical. Matplotlib categorical support is a rather new feature in matplotlib 2.1. Scatter plots can be made using any type of cartesian axis, including linear, logarithmic, categorical or date axes. What is going wrong? Is it possible to make three scatter plots in one plot with labels on the x-axis? It also runs when I only run the first scatter plot and disable the second the third. ![]() ![]() The code runs if I disable the first scatter plot and only run the second and the third. You can use the following basic syntax to add a trendline to a plot in Matplotlib: create scatterplot plt.scatter(x, y) calculate equation for trendline z np.polyfit(x, y, 1) p np.poly1d(z) add trendline to plot plt.plot(x, p (x)) The following examples show how to use this syntax in practice. ![]() It seems like it tries to convert lo_label into something else. The error I get is: could not convert string to float: lo c_pop = Ĭ_labels = Īx1.scatter(c_labels, c_pop, color='black')Īx1.scatter(lo_label, pre_lo, color='green', label='pre-SNEP')Īx1.scatter(lo_label, post_lo, color='red', label='post-SNEP') import matplotlib.pyplot as pltĭefine the variables and make one figure that contains three scatter plots. subplot(321) will divide your figure into a grid with 3 rows and 2 columns (ie space for 6 plots) and then create an axes object for the first (top-left) of. I'm trying to make three scatter plots in one figure.
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