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Data Visualization Articles
Page 14 of 68
How to plot int to datetime on X-axis using Seaborn?
To plot int to datetime on X-axis using Seaborn in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe, df, of two-dimensional, size-mutable, potentially heterogeneous tabular data, with three columns.Create a countplot with int, i.e., dob on the X-axis.Set int to datetime label on the X-axis.To display the figure, use Show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt import pandas as pd import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Data frame with 3 ...
Read MoreHow to build colorbars without attached plot in matplotlib?
To build colorbars without attached plot in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Adjust the subplot layout parameters.Normalize the quaternion in place. Return the norm of the quaternion.Get the colorbar instance (cb) with base colorbar and horizontal orientation.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt import matplotlib as mpl # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create a figure and a set of subplots fig, ax = plt.subplots() # Adjust ...
Read MoreHow to cycle through both colours and linestyles on a matplotlib figure?
To cycle through both colors and linestyles on a matplotlib figure, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Set the current rcParams, withcolors and linestyle.Plot the data points using plot() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt from cycler import cycler # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Set the rcParams with color or linestyle plt.rc('axes', prop_cycle=(cycler('color', ['r', 'g', 'b', 'y']) + cycler('linestyle', [':', '-.', '-', '--']))) # Plot the data points plt.plot([0, 5, 2, ...
Read MoreHow to better rasterize a plot without blurring the labels in matplotlib?
To rasterize a plot in a bettery way without blurring the labels in matplotlib, we can take the following steps.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Axis 0 – Fill the area between the curve with alpha and rasterized=False.Add text to the axes.Axis 1 – Fill the area between the curve with alpha and rasterized=True.Add text to the axes.Axes 2 and 3 – Fill the area between the curve without alpha and rasterized=True and False, respectively.Add text to the axes.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as ...
Read MoreHow to get the properties of a picked object in mplot3d (matplotlib + python)?
To get the properties of picked objects in matplotlib 3d, we can take the following steps.StepsSet 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.Make a scatter plot of random data points.Bind the function *pick_event_method* to the event *pick_event*.Print x, y and z coordinates of the event.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 fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ...
Read MorePlotting profile histograms in Python Matplotlib
In a profile histogram, each bin contains the mean of its entries. To plot profile histograms in Python, we can use the regplot method from Seaborn.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use seaborn.regplot to plot the data and a linear regress model fit. Use the parameter x_bins to bin the x variable into discrete bins. Use fit_reg=True to plot the regression model relating the x and y variables.To display the figure, use Show() method.Exampleimport numpy as np import seaborn as sns from matplotlib import pyplot as plt ...
Read MoreMatplotlib – Difference between plt.subplots() and plt.figure()
plt.figure() − Creates a new figure or activates an existing figure.plt.subplots() − Creates a figure and a set of subplots.Let's take an example to understand the difference between plt.subplots() and plt.figure().StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure. Use plt.figure() method.Create a figure and a set of subplots. Use plt.subplots() method.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 # Create a new figure using plt.figure fig1 = plt.figure("Figure 1 ...
Read MoreMatplotlib – How to show the coordinates of a point upon mouse click?
To create a custom mouse cursor in matplotlib, 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.Bind the function *mouse_event* to the event *button_press_event*.Create x and y data points using numpy.Plot the x and y data points using plot() 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 def mouse_event(event): print('x: {} and y: {}'.format(event.xdata, event.ydata)) fig = plt.figure() cid = fig.canvas.mpl_connect('button_press_event', mouse_event) ...
Read MoreHow to read an input image and print it into an array in matplotlib?
To read an input image and print it into an array in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Read an image from a file into an array. Use plt.imread() method.Print the Numpy array of the image.To turn off the axis, use axis('off') method.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True im = plt.imread("forest.jpg") print("Numpy array of the image is: ", im) im = plt.imshow(im) plt.axis('off') plt.show()OutputIt will produce the following output −On the ...
Read MoreHow to create minor ticks for a polar plot in matplotlib?
To create minor ticks for a polar plot in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create r (radius) and theta data points using numpy.Add a subplot to the current figure.Iterate the points between 0 to 360 with step=10 and plot them to get the ticks.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 # radius and theta for the polar plot r = np.arange(0, 5, 0.1) theta = 2 ...
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