X3,圓= np.loadtxt('MaxMin3.txt', dtype=str, unpack=True) The return value is an instance of FancyBboxPatch and the patch properties like. X2,y2= np.loadtxt('MaxMin2.txt', dtype=str, unpack=True) ax.annotate(local max, xy(3, 1), xycoordsdata, xytext(0.8, 0.95). X1,y1= np.loadtxt('MaxMin1.txt', dtype=str, unpack=True) Set the figure size and adjust the padding between and around the subplots. BTW, my golden rule for Data Visualization is Do it in Seabron if you can do it in Seaborn. To annotate the maximum value in a Pyplot, we can take the following steps. It is built on top of Matplotlib, another vast and deep data visualization library. Works really well with pandas data structures, which is just what you need as a data scientist. Additionally, you may specify a text point xytext (x, y) for the location of the text for this annotation. It is very easy to use and requires less code syntax 2. Also the label is appearing too far from the point overlapping with the legend. You must specify an annotation point xy (x, y) to annotate this point. I am trying to label multiple maximum but unable to display them properly.
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