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Data Visualization Articles
Page 15 of 68
How to plot an animated image matrix in matplotlib?
To plot an animated image matrix in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Make an animation by repeatedly calling a function *update*.Inside the update method, create a 6×6 dimension of matrix and display the data as an image, i.e., on a 2D regular raster.Turn off the axes using set_axis_off().To display the figure, use Show() method.Examplefrom matplotlib.animation import FuncAnimation import matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() def ...
Read MoreHow to put a title for a curved line in Python Matplotlib?
To put a title for a curved line in Python 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 such that the line would be a curve.Plot the x and y data points.Place a title for the curve plot using plt.title() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create x and y data points x = np.linspace(-1, 1, 50) y = 2**x + 1 # Plot ...
Read MoreMatplotlib – How to plot the FFT of signal with correct frequencies on the X-axis?
To plot the FFT (Fast Fourier Transform) of a signal with correct frequencies on the X-axis in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize two variables, N and m, to calculate nu.Create the signal (a sine wave) using numpy. Compute the one-dimensional discrete Fourier Transform.Return the Discrete Fourier Transform sample frequencies.Plot the freq and fourier transform 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 N = 256 t = np.arange(N) m ...
Read MoreWhen is plt.Show() required to show a plot and when is it not?
plt.Show() would help whenever there is no interactive plot.fig.Show() would help to display all the figures if it is interactive.Let's take an example to observe the difference between plt.Show() and fig.Show().StepsOpen iPython shell.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Plot a line using plot() method.Display the figure using Show() method.To display the figure, use Show() method with block=False.Exampleimport numpy as np from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create a new figure fig ...
Read MoreSaving a 3D-plot in a PDF 3D with Python
To save a 3D-plot in a PDF with Python, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Create u, v, x, y and z data points using numpy.Plot a 3D wireframe.Set the title of the plot.Save the current figure using savefig() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111, projection='3d') u, v = np.mgrid[0:2 * np.pi:30j, ...
Read MoreHow to control the border of a bar patch in matplotlib?
To control the border of a bar patch in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a list of heights and a tuple for labels.Use the bar() method with edgecolor in the argument to control the color of the bar patch. Here we have used edgecolor='green'.Set the ticks and labels of the X-axis.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 height = [3, 12, 5, 18, 45] labels = ('P1', 'P2', 'P3', 'P4', ...
Read MoreHow can I plot two different spaced time series on one same plot in Python Matplotlib?
To plot two different spaced time series on one same plot using Matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create x1, y1 and x2 and y2 data points.Create a figure and a set of subplots.Plot the data that contains dates, with (x1, y1) and (x2, y2) data points.Set the major formatter of the X-axis ticklabels.Rotate xtick label by 45 degrees using tick_params() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt from matplotlib.dates import date2num, DateFormatter import datetime as dt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ...
Read MoreHow to increase colormap/linewidth quality in streamplot Matplotlib?
To increase colormap/linewidth quality in streamplot matplotlib, we can take the following stepsStepsSet 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 and then use np.meshgrid() to return the coordinate matrices from the coordinate vectors.Find X and Y using x and y data points.Create a streamplot with x, y, X and Y data points. You can increase the linewidth using the linewidth parameter in the method. Here we have used linewidth=5.Create a colorbar for a ScalarMappable instance, *stream.lines*.To display the figure, use Show() method.Exampleimport numpy ...
Read MoreHow to change the transparency/opaqueness of a Matplotlib Table?
To change the transparency/opaqueness of a matplotlib table, we can atke following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Create a random dataset with 10×3 dimension.Create a tuple of columns.Get rid of the axis markers using axis('off').Create a table with data and columns.Iterate each cell of the table and change its transparency/opaqueness using set_alpha() method.To display the figure, use Show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig, axs = plt.subplots(1, 1) data = np.random.random((10, 3)) ...
Read MoreEmbedding a matplotlib animation into a tkinter frame
To embed a matplotlib animation into a tkinter frame, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a Toplevel widget of Tk which represents mostly the main window of an applicationSet the title of this widget.Add an axes to the current figure and make it the current axes.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make a dummy line plot with linewidth=2.Create the canvas the figure renders into.Create the figure canvas on which to operate.Create a keypress event to ...
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