To display two sympy plots as one Matplotlib plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Transform strings into instances of :class:'Symbol' class.Plot a function of a single variable as a curve.Use the extend method to add all the ... Read More

To plot an area in a Pandas dataframe in Matplotlib Python, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe, i.e., a two-dimensional, size-mutable, potentially heterogeneous tabular data.Return the area between the graph plots.To display the figure, ... Read More

To show the same Matplotlib figure several times in a single iPython notebook, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot the data points on that axes.To show the current figure again, ... Read More

To plot the sine curve on polar axes, 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() methodAdd an '~.axes.Axes' to the figure as part of a subplot arrangement.Get x ... Read More

To find the intersection of two lines segments in Matplotlib and pass the horizontal and vertical lines through that point, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create two lines using slopes (m1, m2) and intercepts (c1 and c2). ... Read More

To show minor tick labels on a log-scale with Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot x and y data points using plot() methodGet the current axis using gca() method.Set ... Read More

To hide lines in Matplotlib, we can use line.remove() method.StepsSet the figure size and adjust the padding between and around the subplots.Create x, y1 and y2 data points using numpy.Make lines, i.e., line1 and line2, using plot() method.To hide the lines, use line.remove() method.Place a legend on the figure at ... Read More

To fill the area under step curve using pyplot, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Ceate random data points, x, y1 and y2, using numpy.To fill the area under the curve, put x and y with ste="pre", using fill_between() ... Read More

To make a boxplot with variable length data in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of data points.Make a box and whisker plot using boxplot() method.To display the figure, use show() method.Examplefrom matplotlib import ... Read More

To save all the open Matplotlib figures in one file at once, we can take follwong steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure (fig1) or activate an existing figure using figure() method.Plot the first line using plot() method.Create a new ... Read More