Something is wrong between the connection between the legend symbol color and the scatter plot error bars. import matplotlib. The problem is that the colors in the plot symbols are completely different from the symbol colors in the legend. The following steps are used to plot scatter graph and add a legend to it are outlined below: Defining Libraries: Import the important libraries which are required for data creation and manipulation ( Numpy and Pandas) and for data visualization ( pyplot from matplotlib). Now, here is the code: import numpy as npĭf2a = pd.DataFrame(np.random.rand(10,5), columns = list('ABCDE'))ĭf2a.insert(0,'x_var_plot',range(1,df2a.shape+1))ĭf2a_err = pd.DataFrame(np.random.rand(df2a.shape,df2a.shape-1), columns = ())ĭf2a_err.insert(0,'x_var_plot',range(1,df2a.shape+1))Ĭolors = iter(cm.rainbow(np.linspace(0, 1, df2a.shape)))įor col in ():Īx.errorbar(df2a, df2a, yerr=df2a_err, fmt='o')Īx.scatter(df2a, df2a, color=next(colors), label=col) There are different colors for all the plotted y-values. Plt.legend(loc='upper right', bbox_to_anchor=(1, -0.I have a scatter plot of multiple y-values for the same x-value, in matplotlib (python 2.7). Markersize=15, fillstyle='left', markeredgewidth=0, Marker='.', linestyle='', markeredgecolor='None', Plt.plot(x, y, c=colors, markerfacecoloralt=colors, import numpy as np from matplotlib.cm import getcmap import matplotlib.pyplot as plt rng np.faultrng (0) x rng. Youll additionally need to segment a sequential colormap to achieve a non-repeating color and pair those colors against the unique IDs. Mask = (cols_true = tc) & (cols_pred = pc) This way matplotlib will infer your IDs as unique entries on your plot. # this would make the 'true' colors nicely grouped # for x and y, suppose some 2D gaussian normal distribution around some centers, using size and color but no label plt.scatter(lon, lat, labelNone. Ĭols_pred = np.random.randint(0, 5, N * 5) # as a demo, take a random number for each predicted color Plot legends give meaning to a visualization, assigning meaning to the various plot. Labels = # suppose these are the labels for the predictionĬolors = list('rgbkm') # a list of 5 colorsĬols_true = np.repeat(range(5), N) # suppose the first N have true color 0, the next N true color 1.
PYTHON SCATTER PLOT MULTIPLE COLOR LEGEND CODE
Here is some code to illustrate the concepts: from matplotlib import pyplot as pltįrom llections import LineCollection
While looping through the colors, plot can generate legend labels with the corresponding bicolored dot.
So, for 5 colors, there are 25 combinations which can be drawn in a loop. Per plot you can only give one type of style. The following also demonstrates how transparency of the markers can be adjusted by giving alpha a value between 0 and 1. This legend guide is an extension of the documentation available at legend () - please ensure you are familiar with contents of that documentation before proceeding with this guide. 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.
PYTHON SCATTER PLOT MULTIPLE COLOR LEGEND FULL
Matplotlib's plot function accepts marker filling styles, which have a possibility of being bicolored, either top-bottom or left-right. Click here to download the full example code Legend guide Generating legends flexibly in Matplotlib. For example: import matplotlib.pyplot as plt from matplotlib import colors as mcolors for color, group in df.groupby(Color): plt.scatter(groupA, groupB, ccolor, alpha0.8, labelcolor) plt.legend() plt. import plotly.express as px df px.data.tips () fig px.scatter (df, x'totalbill', y'tip', color'day', symbol'sex') for i, trace in enumerate (fig.data): name (',') if name 1 ' Male': trace 'name' '' trace 'showlegend'False else: trace 'name' name 0 fig.addtrace (go.Scatter (y None, mode'mar. Playing with linewidth might give help to visualize the true and the predicted colors together. A simple way is to group your data by color, then plot all of the data on one plot. So, you could just iterate through all edge colors and plot them in a loop over the same plot.
scatter accepts an array for either one of them, but not for both. The dots of regular scatter plots can have an interior color and an edge color.
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