Pandas plot scatter alpha1/12/2024 ![]() Img = img.reshape(_width_height() + (3,))įor x, y, c in zip(,, ):įig = plt.figure(figsize=figsize, dpi=dpi, tight_layout=". Img = np.frombuffer(_rgb(), dtype=np.uint8) import numpy as npįrom _agg import FigureCanvasAgg as FigureCanvas Note this solution forfeits access to the original fig object and attributes, so any other modifications to figure should be made before it's drawn. I opted to instead plot each layer separately with alpha=1 and then read in the resulting image with np.frombuffer (as described here), then add the alpha to the whole image and plot overlays using plt.imshow. I also wanted to plot a different shape other than a circle. I had to plot >500000 points, and the shapely solution does not scale well. Here's a hack if you have more than just a few points to plot. That means that the separation needs to be chosen based on the range of your data, and if you plan to make an interactive plot then there's a risk of all the data points suddenly vanishing if you zoom out too much, and stretching if you zoom in too much.Īs you can see, I found 1e-5 to be a good separation for data with a range of. If they're two far apart then the separation will be visible on your plot, but if they're too close together, matplotlib doesn't plot the line at all. Set the color, size, and x & y coordinates using column names. One caveat is that you have to be careful with the spacing between the two points you use to make each circle. Pandas Scatter Plot - Create beauitful scatter plots right from your Pandas DataFrame. I opted to instead plot each layer separately with alpha1 and then read in the resulting image with np.frombuffer (as described here), then add the alpha to the whole image and plot overlays using plt.imshow. Plt.rcParams = 'round'Īx.plot(*expand(x1, y1), lw=20, color="blue", alpha=0.5)Īx.plot(*expand(x2, y2), lw=20, color="red", alpha=0.5)Īnd each color will overlap with the other color but not with itself. I had to plot >500000 points, and the shapely solution does not scale well. With that in mind, you can do this: import numpy as np You see while Matplotlib plots data points as separate objects that can overlap, it plots the line between them as a single object - even if that line is broken into several pieces by NaNs in the data. This is a terrible, terrible hack, but it works. Polygon2 = ptc.Polygon(np.array(polygon2.exterior), facecolor="blue", lw=0, alpha=alpha) ![]() Polygon1 = ptc.Polygon(np.array(polygon1.exterior), facecolor="red", lw=0, alpha=alpha) ![]() Polygons2 =, y2).buffer(size) for i in range(n)]Īx = fig.add_subplot(111, title="Test scatter") Polygons1 =, y1).buffer(size) for i in range(n)] Here is the code : import matplotlib.pyplot as plt I was able to to this sucessfully in an previous version of pandas (1.4.2 I believe) but I am now on a new computer with version 1.5. You can get this scatterplot with Shapely. ![]()
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