To plot 2D math vectors with matplotlib, we can take the following steps−Create vector cordinates using numpy array.Get x, y, u and v data points.Create a new figure or activate an existing figure using figure method.Get the current axis using gca() method.Set x an y limits of the axes.To redraw ... Read More

To wrap long Y label in matplotlib tight layput using setp, we can take the following steps−Create a list of a long strings.Create a tuple of 3 values.Create a figure and add a set of subplots.Limit the Y-axis ticks using ylim() method.Make a horizontal bar plot, using barh() method.Use yticks() ... Read More

To create a standard colorbar for a series of plots, we can take the following steps −Create random data using numpy.Create a figure and a set of subplot using subplots() method, where nrows=1 and ncols=1.Display data as an image.Add an axes to the figure, for colorbar.Create a colorbar where mappable ... Read More

To get a list of all the fonts currently available for matplotlib, we can use the font_manager.findSystemFonts() method.StepsPrint a statement.Use font_manager.findSystemFonts() method to get a list of fonts availabe.Examplefrom matplotlib import font_manager print("List of all fonts currently available in the matplotlib:") print(*font_manager.findSystemFonts(fontpaths=None, fontext='ttf'), sep="")Output/usr/share/fonts/truetype/Nakula/nakula.ttf /usr/share/fonts/truetype/ubuntu/Ubuntu-L.ttf /usr/share/fonts/truetype/tlwg/Loma-BoldOblique.ttf ................................................................. ............................................................................ ................................................................................. ........ ... Read More

To place a top label for colorbars, we can use colorbar's axis to set the title.StepsCreate random data using numpy.Use imshow() method to represent data into an image, with colormap "PuBuGn" and interpolation= "nearest".Create a colorbar for a scalar mappable instance, imSet the title on the ax (of colorbar) using ... Read More

To darken and lighten the color, we can chage the alpha value in the argument of plot() method.Greater the aplha value, darker will be the color.StepsCreate data points for xs and ys using numpy.Plot two lines with different value of alpha, to replicate darker and lighter color of the linesPlace ... Read More

To change the range of the X-axis with datetimes in matplotlib, we can take the following steps −Create a list of x and y, where x stores the datetime and y stores the number.Using subplots method, create a figure and add a set of subplots.Plot x and y data points using plots() method, wehere markerface ... Read More

To change the plot line color from blue to black, we can use setcolor() method−StepsCreate x and y data points using numpy.Plot line x and y using plot() method; store the returned value in line.Set the color as black using set_color() method.To display the figure, use show() method.Exampleimport numpy as ... Read More

To determine the axis size in pixels, we can take the following steps −Create a figure and a set of subplots, using subplots() method, fig and ax.To get the DPI, use fig.dpi. Print the details.Find bounding box in the display box.Find the width and height, using bbox.width and bbox.height.Print the width and ... Read More

To make a multicolored point in matplotlib, we can take the following steps−Initialize two varuables, x and y.Use scatter method with x and y data points with green color having marker size 2000.Use scatter method with x and y data points with red color having marker size 1000.Use scatter method ... Read More