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Articles by Rishikesh Kumar Rishi
Page 10 of 102
Saving multiple figures to one PDF file in matplotlib
To save multiple figures in one PDF file at once, we can take follwong stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure (fig1) or activate and existing figure using figure() method.Plot the first line using plot() method.Create another figure (fig2) or activate and existing figure using figure() method.Plot the second line using plot() method.Initialize a variable, filename, to make a pdf file.Create a user-defined function save_multi_image() to save multiple images in a PDF file.Call the save_multi_image() function with filename.Create a new PdfPages object.Get the number of open figures.Iterate the opened figures and ...
Read MoreHow to show numpy 2D array as grayscale image in Jupyter Notebook?
To show a 2D array as a grayscale image in Jupyter Notebook, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a random data using numpy.Display the data as an image, i.e., on a 2D regular raster, with gray colormap.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Random data points data = np.random.rand(5, 5) # Plot the data using imshow with gray colormap plt.imshow(data, cmap='gray') # ...
Read MoreFilling the region between a curve and X-axis in Python using Matplotlib
To fill the region between a curve and X-axis in Python using Matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot the x and y data points using plot() method.Fill the area between the curve and the X-axis using fill_between() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create x and y data points x = np.linspace(-5, 5, 100) y = np.sin(x) ...
Read MoreHow do I use colorbar with hist2d in matplotlib.pyplot?
To use colorbar with hist2d in matplotlib.pyplot, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable "N" for the number of sample data.Createx and y data points using numpy.Create a figure and a set of subplots using subplots() method.Make a 2D histogram plot using hist2D().Create a colorbar for the hist2d scalar mappable instance.To display the figure, use Show() method.Examplefrom matplotlib.colors import LogNorm import matplotlib.pyplot as plt import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Number of sample data ...
Read MoreHow to use unicode symbols in matplotlib?
To use unicode symbols in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Add text to figure, using text() method with unicode symbols. Here we have used the Unicode chararacter (Δ) which has the character code (0394).To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Unicode symbol plt.text(0.5, 0.5, s=u"\u0394", fontsize=50) # Display the plot plt.show() OutputIt will produce the following output −Now, let's use another Unicode character (\u2734).It will produce the following ...
Read MoreHow to append a single labeled tick to X-axis using matplotlib?
Tp append a single labeled tick to X-axis using matplotlib, we can take the following steps.StepsSet 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() method.Set xticks at a single point.Set the tick label for single tick point.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create x and y data points x = np.linspace(-5, 5, 50) y = np.sin(x) # Plot ...
Read MoreHow to plot a plane using some mathematical equation in matplotlib?
To plot a plane using some mathematical equation in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Using x and y, find the equation of the plane (eq).Create a new figure or activate an existing figure.Get the current axis with projection='3d'.Create a surface plot with x, y and eq data points.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-10, 10, 100) y = np.linspace(-10, 10, 100) ...
Read MoreHow to plot a bar chart for a list in Python matplotlib?
To plot a bar chart for a list in python matplotlib we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Make a list of data points.Make a bar plot with data.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # List of data points data = [0, 1, 3, 2, 1, 5, 2, 1, 4, 2, 4, 0] # Plot bar chart with data points plt.bar(data, data) # Display the plot plt.show() OutputIt will produce the following output −
Read MorePreserve padding while setting an axis limit in matplotlib
To preserve padding while setting axis limit, we can avoid using the tight layout, i.e., plt.rcParams["figure.autolayout"] = False.StepsSet 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() method.Set x and y axes limit.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-10, 10, 100) y = np.sin(x) ** 2 plt.plot(x, y) plt.xlim([0, max(x)+0.125]) plt.ylim([0, max(y)+0.125]) plt.show() OutputIt will produce the following output −
Read MoreHow to show (0,0) on matplotlib graph at the bottom left corner?
To show (0, 0) on matplotlib graph at the bottom left corner, we can use xlim() and ylim() methods.StepsSet the figure size and adjust the padding between and around the subplots.Make lists of data points for x and y.Plotx and y data points.Setx and y axes scale.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.array([0, 1, 3, 2, 1, 5]) y = np.array([0, 2, 4, 4, 3, 3]) plt.plot(x, y) plt.xlim([0, max(x)+0.5]) plt.ylim([0, max(y)+0.5]) plt.show() OutputIt will produce the ...
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