To plot customized legend symbols on a plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Inherit HandlerPatch class, override create artists method, add an elliptical patch to the plot, and return the patch handler.Plot a circle on the plot ... Read More

To plot a single line that continuously changes color, we can take the following steps−Set the figure size and adjust the padding between and around the subplots.Create random x and y data points using numpy.Create a figure and a set of subplots.Iterate the index in the range of 1 to ... Read More

To set the Matplotlib title in bold while using "Times New Roman", we can use fontweight="bold".StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Create x and y data points using numpy.Plot x and y data points using scatter() method.Set ... Read More

To plot a 3D surface from x, y and z scatter data in Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the figure as ... Read More

To get the (x, y) values of a line that is plotted by a contour plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a 3D contour plot using contour() method.Get the contour plot collections and get the paths.To ... Read More

To animate a time-ordered sequence of Matplotlib plots, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an axes to the figure as part of a subplot arrangement.Return the first recurrence after ... Read More

To fill the area under a curve in Matplotlib python on log scale, we can take the following steps−Set the figure size and adjust the padding between and around the subplots.Create x, y1 and y2 data points using numpy.Plot x, y1 and y2 data points using plot() method.Fill the area ... Read More

To force errorbars to render last with matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Get the current axis using gca() method.Plot the list of linesPlot y versus ... Read More

Matplotlib provides a number of colormaps, and others can be added using :func:'~matplotlib.cm.register_cmap'. This function documents the built-in colormaps, and will also return a list of all registered colormaps, if called.Examplefrom matplotlib import pyplot as plt cmaps = plt.colormaps() print("Possible color maps are: ") for item in ... Read More

To plot multiple time-series data frames into a single plot using Pandas, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas data frame with time series.Set the time series index for plot.Plot rupees and dollor on the plot.To ... Read More