legend_elements ( ** kw ), loc = "lower right", title = "Price" ) plt. cmap ( 0.7 ), fmt = "$ ", func = lambda s : np. kw = dict ( prop = "sizes", num = 5, color = scatter. The following also demonstrates how transparency of the markers can be adjusted by giving alpha a value between 0 and 1. 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. 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. I have attached a sample plot to illustrate the problem. Is there any way to manually set the color for the legend. For example: import matplotlib.pyplot as plt import numpy as np import pandas as pd np.ed(1974) Generate Data num 20 x, y np.random. Its better to just use plot for discrete categories like this. The *fmt* ensures to show the price # in dollars. 1 Answer Sorted by: 4 The matplotlib scatter example that addresses this problem also uses a loop, so that is probably the intended usage: If your larger goal is to just make plotting and labeling categorical data more straightforward, you should consider Seaborn. And then generating a legend by doing: plt.legend(str(x) for x in np.unique(labels)) However, for each label in the legend the corresponding color is the same (not the color in the plot). You can use scatter for this, but that requires having numerical values for your key1, and you wont have a legend, as you noticed. A 2D array in which the rows are RGB or RGBA. 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. Possible values: A scalar or sequence of n numbers to be mapped to colors using cmap and norm. add_artist ( legend1 ) # Produce a legend for the price (sizes). Multiple traces can be linked to the same color axis. legend_elements ( num = 5 ), loc = "upper left", title = "Ranking" ) ax. Traces which support continuous colorcan also be associated with color axes in the layout via the coloraxisattribute. 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. To build a scatter plot, we require two sets of data where one set of arrays represents the x axis and the other set of arrays represents the y axis data. To represent a scatter plot, we will use the matplotlib library. The dots in the plot are the data values. The positions are measured from 0,0 being the lower left of the current ax, to 1,1: the upper left of the current ax.This doesnt include the padding for titles etc. If False, no legend data is added and no legend is drawn. If auto, choose between brief or full representation based on number of levels. (The default loc is best which means you dont know beforehand where it would end up). If full, every group will get an entry in the legend. uniform ( 1, 10, size = 40 ) fig, ax = plt. Scatter plot in Python is one type of a graph plotted by dots in it. To position the legend, it is important to set the loc parameter, being the anchor point. import numpy as npĬmap = get_cmap('viridis', len(unique_ids))įor _id, color in zip(unique_ids, lors):Īx.scatter(x, y, label=_id, color=color)Īx.Volume = np. You'll additionally need to segment a sequential colormap to achieve a non-repeating color and pair those colors against the unique IDs. This way matplotlib will infer your IDs as unique entries on your plot. legend_elements to do this: import pandas as pdįig, ax = plt.subplots(figsize=(10, 8),dpi = 80)Īx.legend(*scatter.legend_elements(num=list(np.unique(ID))),Īx.tick_params(axis = 'x',labelrotation = 45)Īlternatively, you can iterate over your unique IDs and add each a scatter for each unique ID. You can pass the unique IDs you want a label to be created for into the num argument of. Matpotlib is currently inferring you colors to be on a continuous scale instead of a categorical one.
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