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Articles by Rishikesh Kumar Rishi
Page 38 of 102
Display two Sympy plots as one Matplotlib plot (add the second plot to the first)
To display two sympy plots as one Matplotlib plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Transform strings into instances of :class:'Symbol' class.Plot a function of a single variable as a curve.Use the extend method to add all the series of plot2 (p2) in plot1 (p1).To display the figure, use show() method.Examplefrom sympy import symbols from sympy.plotting import plot from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = symbols('x') p1 = plot(x*x, show=False) p2 = plot(x, show=False) p1.extend(p2) p1.show()Output
Read MoreHow do I show the same Matplotlib figure several times in a single IPython notebook?
To show the same Matplotlib figure several times in a single iPython notebook, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot the data points on that axes.To show the current figure again, use fig.show() method.ExampleIn [1]: %matplotlib auto Using matplotlib backend: Qt5Agg In [2]: import matplotlib.pyplot as plt In [3]: plt.rcParams["figure.figsize"] = [7.50, 3.50] ...: plt.rcParams["figure.autolayout"] = True In [4]: fig, ax = plt.subplots() In [5]: ax.plot([2, 4, 7, 5, 4, 1]) Out[5]: [] In [6]: fig.show()Output
Read MoreHow to plot sine curve on polar axes using Matplotlib?
To plot the sine curve on polar axes, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() methodAdd an '~.axes.Axes' to the figure as part of a subplot arrangement.Get x and y data points using numpy.Plot x and y data points using plot() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(projection='polar') x = np.linspace(-5, 5, 100) y = ...
Read MoreHow do I find the intersection of two line segments in Matplotlib?
To find the intersection of two lines segments in Matplotlib and pass the horizontal and vertical lines through that point, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create two lines using slopes (m1, m2) and intercepts (c1 and c2). Initialize the slopes and intercept values.Create x data points using numpy.Plot x, m1, m2, c2 and c1 data points using plot() method.Using intercepts and slope values, find the point of intersection.Plot the horizontal and vertical lines with dotted linestyle.Plot xi and yi points on the plot.To display the figure, use ...
Read MoreHow to show minor tick labels on a log-scale with Matplotlib?
To show minor tick labels on a log-scale with Matplotlib, we can take the following steps −Set 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() methodGet the current axis using gca() method.Set the yscale with log class by name.Change the appearance of ticks and tick label using ick_params() method.Set the minor axis formatter with format strings to format the tick.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt from matplotlib.ticker import FormatStrFormatter plt.rcParams["figure.figsize"] = [7.50, 3.50] ...
Read MoreHow to fill the area under a step curve using pyplot? (Matplotlib)
To fill the area under step curve using pyplot, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Ceate random data points, x, y1 and y2, using numpy.To fill the area under the curve, put x and y with ste="pre", using fill_between() method.Plot (x, y1) and (x, y2) lines using plot() method with drawstyle="steps" method.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-10, 10, 100) y1 = np.sin(x) y2 = np.cos(x plt.fill_between(x, y1, step="pre", alpha=0.4) ...
Read MoreBoxplot with variable length data in Matplotlib
To make a boxplot with variable length data in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of data points.Make a box and whisker plot using boxplot() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = [[2, 4, 1, 3], [0, 4, 3, 2], [0, 0, 1, 0]] plt.boxplot(data) plt.show()Output
Read MoreSaving all the open Matplotlib figures in one file at once
To save all the open Matplotlib figures in one file at once, we can take follwong steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure (fig1) or activate an existing figure using figure() method.Plot the first line using plot() method.Create a new figure (fig2) or activate an existing figure using figure() method.Plot the Second line using plot() method.Initialize a variable, filename, to make a pdf file.Create a user-defind function, save_multi_image, and call it to save all the open matplotlib figures in one file at once. Create a new PdfPages object, pp.Get the ...
Read MoreHow to plot collections.Counter histogram using Matplotlib?
To plot a histogram, with collections.Counter, we can use bar() method. In bar() method, we can use collections.counter() to get the frequency for each element. Put the elements and their frequency as height.StepsSet the figure size and adjust the padding between and around the subplots.Make a list of a data points.Get the dictionary, d, using collections.Counter().Make bar plot with d.keys() and d.values().To display the figure, use show() method.Exampleimport collections from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = [0, 1, 2, 4, 1, 3, 0, 4, 1, 4, 3, 5, 6, 5, ...
Read MoreHow to show the title for the diagram of Seaborn pairplot() or PridGrid()? (Matplotlib)
To show the title for the diagram for Seaborn pairplot(), we can use pp.fig.suptitle() method.StepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe, i.e., a two-dimensional, size-mutable, potentially heterogeneous tabular data.Plot pairwise relationships in a dataset.Add a centered title to the figure.To display the figure, use show() method.Exampleimport seaborn as sns import pandas as pd import numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(np.random.random((5, 5)), columns=["a", "b", "c", "d", "e"]) pp = ...
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