Placing legend in matplotlib with default positionTo place the visually appealing legends in matplotlib, we need to follow a few easy steps:Create a plot using the plot() function from matplotlib.pyplot module. Add a label to the plot. Labels represent the name of the plot for the x and ...
Legend is simply the description of various elements in a figure. We can generate a legend of scatter plot using thematplotlib.pyplot.legendfunction. Add a Legend to the 2D Scatter Plot in Matplotlib importnumpyasnpimportmatplotlib.pyplotasplt x=[1,2,3,4,5]y1=[i**2foriinx]y2=[2*i+...
How to add a legend to the plots? For example, if using several moving averages it will be useful to show a legend to map moving averages to line plots. Is clear how this is done using matplotlib but I did not see an example of how to do so using the mplfinance package. TIA, ...
Change the Shape of a Legend Placed Outside the Plot in Matplotlib Let’s suppose that we want to place the legend outside of the plot, but this time at the top position. It would make much more sense to change the shape of the legend so that it’s visualized horizontally rather than...
As multiple functions can be drawn in a single plot; ‘labels’ are the way to provide information about different functions in the plot and labels are created using ‘Legends’ in Python. Examples to Implement Matplotlib Legend Let us now understand how to create plots and give them labels,...
However, it’s worth noting that thelegend()function is designed to add a single legend to a plot. Attempting to add more than one legend using this function will result in a MATLAB error. In order to overcome this limitation and add custom legends that aren’t directly related to the gr...
How to Add and Change Seaborn Legend? The below example shows that by default legend will add to the graph. In the below example, we can see that by default stud1 and stud2 legend will automatically added. Code: importpandasaspdimportmatplotlib.pyplotaspltimportseabornassns plot=pd.DataFrame...
import matplotlib.pyplot as plt import numpy as np x = np.arange(10) fig = plt.figure() ax = plt.subplot(111) for i in xrange(5): ax.plot(x, i * x, label='$y = %ix$' % i) ax.legend(bbox_to_anchor=(1.1, 1.05)) plt.show() https://i.stack.imgur.com/OtE5Um.png...
You can add titles, labels, and other visual enhancements usingmatplotlibfunctions likeplt.title(),plt.xlabel(), andplt.ylabel(). Use thestacked=Trueoption for stacked bar plots, and set thewidthparameter to control bar width in bar plots. ...
import matplotlib.pyplot as plt import numpy as np # Create a user-defined function to plot the graph def legend_outside(x,y1,y2): # Create the figure object fig = plt.figure(figsize=(9, 9)) # Create the axes object ax = plt.subplot(111) ...