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Articles by Rishikesh Kumar Rishi
Page 77 of 102
How to remove the label on the left side in matplotlib.pyplot pie charts?
To remove the label on the left side in a matplotlib pie chart, we can take the following steps −Create lists of hours, activities, and colors.Plot a pie chart using pie() method.To hide the label on the left side in matplotlib, we can use plt.ylabel("") with ablank string.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True hours = [8, 1, 11, 4] activities = ['sleeping', 'exercise', 'studying', 'working'] colors = ["grey", "green", "orange", "blue"] plt.pie(hours, labels=activities, colors=colors, autopct="%.2f") plt.ylabel("") plt.show()Output
Read MoreHow can I display text over columns in a bar chart in Matplotlib?
To display text over columns in a bar chart, we can use text() method so that we could place text at a specific location (x and y) of the bars column.StepsCreate lists for x, y and percentage.Make a bar plot using bar() method.Iterate zipped x, y and percentage to place text for the bars column.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = ['A', 'B', 'C', 'D', 'E'] y = [1, 3, 2, 0, 4] percentage = [10, 30, 20, 0, 40] ax = plt.bar(x, y) for x, y, p in zip(x, y, percentage): ...
Read MoreHow to handle an asymptote/discontinuity with Matplotlib?
To handle an asymptote/discontinuity with matplotlib, we can take the following steps −Create x and y data points using numpy.Turn off the axes plot.Plot the line with x and y data points.Add a horizontal line across the axis, x=0.Add a vertical line across the axis, y=0.Place legend for the curve y=1/x.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 x = np.linspace(-1, 1, 100) y = 1 / x plt.axis('off') plt.plot(x, y, label='y=1/x') plt.axhline(y=0, c='red') plt.axvline(x=0, c='red') plt.legend(loc='upper left') plt.show()Output
Read MoreWhat is the preferred way to set Matplotlib figure/axes properties?
To set the properties of a plot, we can get the current axis of the plot. After that, we can perform several set_* methods to set the properties of the plot.StepsCreate a figure and a set of subplots using subplots() method with figsize=(5, 5).Create x and y data points using numpy.Plot x and y using plot() method.Set the title and labels (for X and Y axis) using set_xlabel() and set_ylabel() methods.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 fig, ax = plt.subplots() x = np.linspace(-1, 1, 10) y = ...
Read MoreHow to remove gaps between bars in Matplotlib bar chart?
To remove gaps between bars, we can change the align value to center in the argument of bar() method.StepsCreate a dictionary called data with two keys, milk and water.Get the list of keys and values in the dictionay.Using subplots() method, create a figure and add a set of two subplots.On axis 2, use bar method to plot bars without gaps. Set the width attribute as 1.0. Set the title using set_title() method.Use tight_layout() to adjust the padding between and around the subplots.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = {'milk': 12, 'water': ...
Read MoreRotate theta=0 on a Matplotlib polar plot
To set theta=0 on a matplotlib polar plot, we can take the following steps −Create random theta in the range of 0 to 100; convert them into radian.Using set_theta_zero_location() method, we can set the location of theta to 0.Plot theta_in_rad and data_r using plot() method.Set the title of the plot using title() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import random plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True theta_in_rad = [float(i) * np.pi / 180.0 for i in range(0, 100, 10)] data_r = random.sample(range(70, 90), 10) ax = plt.subplot(111, polar=True) ax.set_theta_zero_location("W") ax.plot(theta_in_rad, data_r, color='r', linewidth=3) ax.set_title("Example", ...
Read MoreWhat is the difference between plt.close() and plt.clf() in Matplotlib?
plt.figure() - Create a new figure or activate an existing figure.plt.figure().close() - Close a figure window.close() by itself closes the current figureclose(h), where h is a Figure instance, closes that figureclose(num) closes figure number numclose(name), where name is a string, closes the figure with that labelclose('all') closes all the figure windowsplt.figure().clear() - It is the same as clf.plt.cla() - Clear the current axes.plt.clf() - Clear the current figure.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-1, 1, 10) y = np.linspace(1, 2, 10) plt.plot(x, y, c='red') plt.title("First Plot") plt.show() ...
Read MoreHow to add a variable to Python plt.title?
To add a varaible to Python plt.title(), we can take the following steps −Create data points for x and y using numpy and num (is a variable) to calculate y and set this in title.Plot x and y data points using plot() method with red color.Set the title of the curve with variable num.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 x = np.linspace(-1, 1, 10) num = 2 y = num ** x plt.plot(x, y, c='red') plt.title(f"y=%d$^x$" % num) plt.show()Output
Read MoreHow to plot data from multiple two-column text files with legends in Matplotlib?
To plot data from multiple two-column text files with legends in matplotlib, we can take the following steps −Import genfromtxt from pylab. It has several options to read data from a text file and plot the data.Read two text files, test.txt and test1.txt (having two columns of data), using genfromtxt and store the data in two variables, firstfiledata and secondfiledata.Plot the data using plot() method. label will be displayed as the legend.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt; from pylab import genfromtxt; plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True firstfiledata = genfromtxt("test.txt"); secondfiledata = genfromtxt("test1.txt"); plt.plot(firstfiledata[:, 0], firstfiledata[:, 1], label="test.txt ...
Read MoreHide Matplotlib descriptions in Jupyter notebook
To hide matplotlib descriptions of an instance while calling plot() method, we can take the following steps −Open Ipython instance.import numpy as npfrom matplotlib, import pyplot as pltCreate points for x, i.e., np.linspace(1, 10, 1000)Now, plot the line using plot() method.To hide the instance, use plt.plot(x); i.e., (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]: []
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