If you don’t want to use a for loop (which can be very slow for large lists) You can use the scatter command as is with an RGB color list, but you need to specify the colors as a vector of RGB (or RGBA) values between 0 and 1 X = [0, 1, 2] Y … Read more
I think @Evert has the right answer: plt.scatter(dates,values) plt.plot(dates, values) plt.show() Which is pretty much the same as plt.plot(dates, values, ‘-o’) plt.show() You can replace -o with another suitable format string as described in the documentation. You can also split the choices of line and marker styles using the linestyle= and marker= keyword arguments.
Replace edgecolors=None with linewidth=0 Something like: g=sns.scatterplot(x=”length”, y=”coverage”, data=df, hue=”Products”, linewidth=0, alpha = 0.7)
Interactive selection in ggplotly with geom_hex() scatterplot
Basically, no, there isn’t. Layout engines that handle placing map labels similar to this are surprisingly complex and beyond the scope of matplotlib. (Bounding box intersections are actually a rather poor way of deciding where to place labels. What’s the point in writing a ton of code for something that will only work in one … Read more
Yes, interesting question. You can get this scatterplot with Shapely. Here is the code : import matplotlib.pyplot as plt import matplotlib.patches as ptc import numpy as np from shapely.geometry import Point from shapely.ops import cascaded_union n = 100 size = 0.02 alpha = 0.5 def points(): x = np.random.uniform(size=n) y = np.random.uniform(size=n) return x, y … Read more
Where would this bx be passed into? You ought to repeat the second call to plot, not the first, so there is no need for bx. In detail: plot takes an optional ax argument. This is the axes it draws into. If the argument is not provided the function creates a new plot and axes. … Read more
You simply call the scatter function twice, matplotlib will superimpose the two plots for you. You might want to specify a color, as the default for all scatter plots is blue. This is perhaps why you were only seeing one plot. import numpy as np import pylab as plt X = np.linspace(0,5,100) Y1 = X … Read more