Where region_colors.values() are all unique values from your DataFrame in the form of a dictionary with their colours. We will use the () method to describe and label the elements of the graph and distinguishing different plots from the same graph. If you need to create a custom legend with multiple options you can use Python list comprehensions like: custom =, , marker='.', color=i, linestyle='None', markersize=25) for i in region_colors.values()] In order to plot the Scatterplot we generate 2 lists of random integers by: x = np.random.normal(0,1,15)Īnd list of random colors by: colors = Ĭustom Scatterplot legend with multiple options legendelements ('sizes'): import numpy as np import matplotlib.pyplot as plt N 50 x np.random.rand (N) y np.random.rand (N) a2 (N) sc plt.scatter (x, y, sa2, alpha0.5) plt.legend (sc.legendelements ('sizes', num6)) plt. Next we set the legend labels, the font size and the legend position by: plt.legend(custom,, loc='upper left', fontsize=15) Is shown in the legend and the automatic mechanism described aboveīy: custom =, , marker='.', markersize=20, color='b', linestyle='None'), (x, y, sNone, cNone, markerNone, cmapNone, normNone, vminNone, vmaxNone, alphaNone, linewidthsNone,, edgecolorsNone, plotnonfiniteFalse, dataNone, kwargs) source. The following also demonstrates how transparency of the markers can be adjusted by giving alpha a value between 0 and 1. Use this together with labels, if you need full control on what Scatter plots with a legend To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. In order to create custom legend with Matplotlib and Scatterplot we follow next steps:įirst we start with creating the legend handles which are described as:Ī list of Artists (lines, patches) to be added to the legend. Notebook Explanation of custom Scatterplot legend Plt.legend(custom,, loc='upper left', fontsize=15) import randomĬustom =, , marker='.', markersize=20, color='b', linestyle='None'), The example is showing a simple Scatterplot of few random points. In this short post you can find an example on how to add custom legend in Matplotlib and Python. legend_elements ( ** kw ), loc = "lower right", title = "Price" ) plt. Then use ax.legend () which will recognize the label and add legends. Plot your cluster one by one with kwarg label. cmap ( 0.7 ), fmt = "$ ", func = lambda s : np. scatter-plot Share Improve this question Follow edited May 11 at 17:31 Trenton McKinney 55.6k 33 138 151 asked at 17:54 Vince 195 1 2 7 1 Maybe try check the example. kw = dict ( prop = "sizes", num = 5, color = scatter. Note how we target at 5 elements here, but obtain only 4 in the # created legend due to the automatic round prices that are chosen for us. The *fmt* ensures to show the price # in dollars. In this example, the last two scatter traces display on the second legend, 'legend2'. Specify more legends with legend'legend3', legend'legend4' and so on. For a second legend, set legend'legend2'. To have multiple legends, specify an alternative legend for a trace using the legend property. Because we want to show the prices # in dollars, we use the *func* argument to supply the inverse of the function # used to calculate the sizes from above. By default, all traces appear on one legend. add_artist ( legend1 ) # Produce a legend for the price (sizes). legend_elements ( num = 5 ), loc = "upper left", title = "Ranking" ) ax. Even though there are 40 different # rankings, we only want to show 5 of them in the legend. scatter ( volume, amount, c = ranking, s = 0.3 * ( price * 3 ) ** 2, vmin =- 3, vmax = 3, cmap = "Spectral" ) # Produce a legend for the ranking (colors). subplots () # Because the price is much too small when being provided as size for ``s``, # we normalize it to some useful point sizes, s=0.3*(price*3)**2 scatter = ax. uniform ( 1, 10, size = 40 ) fig, ax = plt.
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