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Matplotlib Articles
Page 83 of 91
How to hide in IPython notebook?
To hide matplotlib.lines.Line2D instance while calling the plot() method, we can take the following steps −Import numpy as np.From matplotlib, import pyplot as plt.Create points for x, i.e., np.linspace(1, 10, 1000)Now plot the line using the plot() method.To hide the instance, use plt.plot(x); (with semi colon)Or, use _ = plt.plot(x).ExampleIn [1]: import numpy as np In [2]: from matplotlib import pyplot as plt In [3]: x = np.linspace(1, 10, 1000) In [4]: plt.plot(x) Out[4]: [] In [5]: plt.plot(x); In [6]: _ = plt.plot(x) In [7]:OutputOut[4]: []
Read MoreEmbedding small plots inside subplots in Matplotlib
To embed small plots inside subplots, we can take the following Steps −Using subplots() method, create a figure and a set of subplots (fig, ax1).On ax1, plot a line with color red, line width=4, label=”outer plot”.Using add_axes(), add an axis, i.e., ax2 with l, b, h and w values.Plot the same points (Step 2) usins the plot() method, with color green, line width=3, label=”inside plot”.Set the legend on both the plots using the legend() method.To display the figure, use the show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax1 = plt.subplots() ax1.plot([1, 4, ...
Read MoreHow to change the figuresize using Seaborn factorplot in Matplotlib?
To change the figuresize using Seaborn factorplot, we can take the following Steps −Load the exercise data using load_dataset() method.Using factorplot() method, change figure size by customising the size and aspect values.To display the figure, use the show() method.Exampleimport seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True exercise = sns.load_dataset("exercise") sns.factorplot("kind", "pulse", "diet", exercise, kind="point", size=5, aspect=2) plt.show()Output
Read MoreHow to set the font size of Matplotlib axis Legend?
To set the font size of matplotlib axis legend, we can take the following steps −Create the points for x and y using numpy.Plot x and y using the plot() method with label y=sin(x).Title the plot using the title() method.To set the fontsize, we can override rcParams legend fontsize by value 20.Use the legend() method, and fit the legend at the top-right position.To display the figure, use the show() method.Exampleimport numpy as np from matplotlib import pyplot as plt import matplotlib plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 10, 50) y = np.sin(x) plt.plot(x, y, c="red", lw=7, label="y=sin(x)") ...
Read MoreShow the origin axis (x,y) in Matplotlib plot
To show the origin, we can take the following Steps −Create the points x, y1 and y2 using numpy.Plot the sine and cosine curves using plot() methods.Plot the vertical line, i.e., x=0.Plot the horizontal line, i.e., y=0.Intersection point of (Step 3 and 4), could be the origin.To display the label of lines, use legend() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 10, 50) y1 = np.sin(x) y2 = np.cos(x) plt.plot(x, y1, c="orange", label="y=sin(x)") plt.plot(x, y2, c="green", label="y=cos(x)") plt.axvline(x=0, c="red", label="x=0") plt.axhline(y=0, c="yellow", ...
Read MoreHow to change the color of data points based on some variable in Matplotlib?
To change the color of data points based on some variable in matplotlib, we can take the following steps −Create x, y and c variables using numpy.Plot the scatter points using x, y and for color, use c (Step 1).To display the image, use the show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(1, 20, 50) y = np.log(x) c = np.random.randint(x) plt.scatter(x, y, c=c) plt.show()Output
Read MoreHow to make pylab.savefig() save image for 'maximized' window instead of default size in Matplotlib?
To save image for maximized window instead of default size, we can use the following Steps −Create figure with figsize=(7.50, 3.50), using the figure() method.Plot the lines using the plot() method with list, color=”red”, and linewidth=2.Save the figure using the savefig() method.To display the figure, use the show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() plt.plot([1, 3, 7, 3, 1], c="red", lw=2) plt.savefig("full_image.png") plt.show()Output
Read MoreHow can I show figures separately in Matplotlib?
To show multiple figures in matplotlib, we can take the following Steps −To create a new figure, or activate an existing figure, use the figure() method. (Create two figures namely, Figure1 and Figure2).Plot the lines with the same lists (colors red and green and linewidth 2 and 5).Set the title of the plot over both the figures.To display the figure, use the show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig1 = plt.figure("Figure 1") plt.plot([1, 3, 7, 3, 1], c="red", lw=2) plt.title("I am the part of figure 1") fig2 = plt.figure("Figure 2") plt.plot([1, 3, ...
Read MoreAutomatically position text box in Matplotlib
To position a textbox automatically in matplotlib, we can take the following Steps −Create xpoints from 1 to 2 and 100 samples.Create y1points and y2points using xpoints (Step 1) and numpy.Plot xpoints, y1points and y2points using the plot() method.To set the label, use the legend() method. It will help to position the text box.To display the figure, use the show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True xpoints = np.linspace(1, 2, 100) y1points = np.log(xpoints) y2points = np.exp(xpoints) plt.plot(xpoints, y1points, label="Log") plt.plot(xpoints, y2points, label="Exp") plt.legend() plt.show()Output
Read MoreWhat are the differences between add_axes and add_subplot in Matplotlib?
Definingadd_axes − Add an axes to the figure.add_subplot − Add an axes to the figure as part of a subplot arrangement.StepsCreate a new figure, or activate an existing figure, using the figure() method.Add an axes to the figure as part of a subplot arrangement where nrows=2, ncols=2. At index 1, add the title "subtitle1" and at index 2, add the title "subplot2".Create points for four rectangles and use add_axes() method to add an axes to the figure.To display the figure, use the show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() fig.add_subplot(221) plt.title("subplot1") fig.add_subplot(222) ...
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