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Articles by Rishikesh Kumar Rishi
Page 48 of 102
How to embed an interactive Matplotlib plot on a webpage?
To show a plot on a webpage such that the plot could be interactive, we can take the following steps −Install Bokeh and import figure, show, and output_file.Configure the default output state to generate the output saved to a file when:func:'show' is called.Create a new Figure for plotting.Render the images loaded from the given URLs.Immediately display a Bokeh object or application.Examplefrom bokeh.plotting import figure, show, output_file output_file('image.html') p = figure(x_range=(0, 1), y_range=(0, 1)) p.image_url(url=['bird.jpg'], x=0, y=1, w=0.8, h=0.6) show(p)OutputWhen we execute the code, it will show the following image on your default browser.You can move the image around ...
Read MoreCreate a legend with Pandas and Matplotlib.pyplot
To create a legend with Pandas and matplotib.pyplot(), we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a two-dimensional, size-mutable, potentially heterogeneous tabular data.Plot the dataframe instance with bar class by name and legend is True.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() df = pd.DataFrame({'Numbers': [3, 4, 1, 7, 8, 5], 'Frequency': [2, 4, 1, 4, 3, 2]}) df.plot(ax=ax, kind='bar', legend=True) plt.show()Output
Read MoreFrequency plot in Python/Pandas DataFrame using Matplotlib
To show a frequency plot in Python/Pandas dataframe using Matplotlib, 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.Make a two-dimensional, size-mutable, potentially heterogeneous tabular data.Return a Series containing the counts of unique values.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() df = pd.DataFrame({'numbers': [2, 4, 1, 4, 3, 2, 1, 3, 2, 4]}) df['numbers'].value_counts().plot(ax=ax, kind='bar', xlabel='numbers', ylabel='frequency') plt.show()Output
Read MorePlotting power spectral density in Matplotlib
To plot Power Spectral Density in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, dt.Create t, nse , r, cnse, s, and r data points using numpyCreate a figure and a set of subplots.Plot t and s data using plot() method.Plot the power spectral density.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 dt = 0.01 t = np.arange(0, 10, dt) nse = np.random.randn(len(t)) r = np.exp(-t / 0.05) cnse = np.convolve(nse, ...
Read MoreHow do I print a Celsius symbol with Matplotlib?
To print Celsius symbol with Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, N.Create T and P data points using numpy.Plot T and P using plot() method.Set the label for the X-axis.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 N = 10 T = np.random.rand(N) P = np.random.rand(N) plt.plot(T, P) plt.xlabel("$Temperature {^\circ}C$") plt.show()Output
Read MoreAutomated legend creation in Matplotlib
To automate legend creation in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a variable, N, for number of sample data.Create x, y, c and s data using numpy.Create a figure and a set of subplots using subplots() method.Plot x and y data points with different colors and sizes.Place a legend on the axes.Add an artist to the figure.Create legend handles and labels for a PathCollection.Again, place a legend on the axes for sizes.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np ...
Read MoreHow to plot a nested pie chart in Matplotlib?
To plot a nested pie chart in Matplotlib, 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.Initialize a variable size, create vals, cmap, outer_colors, inner_colors data using numpy.Use pie() function to make pie charts.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 fig, ax = plt.subplots() size = 0.3 vals = np.array([[60., 32.], [37., 40.], [29., 10.]]) cmap = plt.get_cmap("tab20c") outer_colors = cmap(np.arange(3)*4) inner_colors = cmap([1, 2, 5, 6, 9, ...
Read MoreHow to refresh text in Matplotlib?
To refresh text in Matplotlib, 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.Add text to the axes.Write customized method to update text based on the keys "z" and "c".Bind the function action with key_press_event.Draw the canvas that contains the figure.Animate the figure with texts.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, animation plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots() text = ax.text(.5, .5, 'First Text') def action(event): if event.key == "z": ...
Read MoreHow to make xticks evenly spaced despite their values? (Matplotlib)
To make xticks evenly spaced despite their values, we can use set_ticks() and set_ticklabels() methods.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Create a figure and a set of subplots using subplots() method.Plot x and y data points on axis 1.Set xticks using xaxis.set_ticks() method.Plot x and y data points on axis 2.Set xticks and ticklabels using xaxis.set_ticks() and xaxis.set_ticklabels() 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.array([1, 1.5, ...
Read MoreStuffing a Pandas DataFrame.plot into a Matplotlib subplot
To stuff a Pandas dataframe plot into a Matplotlib subplot, 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, two axes.Create a Pandas dataframe using DataFrame.Use DataFrame.plot() method to plot.To display the figure, use show() method.Exampleimport pandas as pd import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, (ax1, ax2) = plt.subplots(2) df = pd.DataFrame(dict(name=["Joe", "James", "Jack"], age=[23, 34, 26])) df.set_index("name").plot(ax=ax1) df.set_index("name").plot(ax=ax2) plt.show()Output
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