Articles on Trending Technologies

Technical articles with clear explanations and examples

How to plot a wav file using Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 6K+ Views

To plot a .wav file using matplotlib, we can take following the steps −To read a .wav file, we can use the read() method.After reading the .wav file, we will get a tuple. At the 0 th index, rate would be there and at the 1st index, array sample data.Use the plot() method to plot the .wav file.Set y and x labels using ylabel and xlabel with “Amplitude” and “Time” label, respectively.To display the figure, use the show() method.Examplefrom scipy.io.wavfile import read import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True input_data = read("my_audio.wav") audio = input_data[1] plt.plot(audio[0:1024]) plt.ylabel("Amplitude") plt.xlabel("Time") plt.show()Output

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Increase the distance between the title and the plot in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 5K+ Views

To increase the distance between the title and the plot in matplotlib, we can take the following steps −Create point x using numpy.Create point y using numpy sin.Set the title of the plot. After changing the value y (in argument), we can increase or decrease the distance between the title and the plot.Plot x and y points using the plot() method, where color is red and line width is 2.Ti 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 x = np.linspace(1, 10, 1000) y = np.sin(x) ttl = ...

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How do I write a Latex formula in the legend of a plot using Matplotlib inside a .py file?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 5K+ Views

LaTeX is a typesetting language for producing scientific documents. We use a very small part of the language for writing mathematical notation. Jupyter notebook recognizes LaTeX code written in markdown cells and renders the symbols in the browser using the MathJax JavaScript library.To write a LaTeX formula in the legend of a plot, we can take the following steps −Create data points for x.Create data point for y, i.e., y=sin(x).Plot the curve x and y with LaTex representation.To activate the label, use the legend() method.To display the figure, use the show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] ...

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How to draw grid lines behind Matplotlib bar graph?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 3K+ Views

To draw grid lines behind matplotlib bar graph, we can take the following Steps −Make a list of numbers, i.e., data.Make a bar using the bar() method, by passing data, color='red' and alpha = 0.5. The alpha blending value should be between 0 (transparent) and 1 (opaque).To configure the grid lines, use the grid() method, with color='yellow', linewidth=1, axis='both' and alpha=0.5.To display the figure, show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = [3, 5, 9, 15, 12] plt.bar(range(len(data)), data, color='red', alpha=0.5) plt.grid(color='yellow', linewidth=1, axis='both', alpha=0.5) plt.show()Output

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Plot parallel coordinates in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 551 Views

To plot parallel coordinates, we can take the following Steps −Load dataset iris using Seaborn (Need internet).Pass the loaded data into the parallel_coordinates() method, which will help in parallel plotting.To display the figure, use the show() method.Exampleimport matplotlib.pyplot as plt from pandas.plotting import parallel_coordinates import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = sns.load_dataset('iris') parallel_coordinates(data, 'species', colormap=plt.get_cmap("Set2")) plt.show()Output

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How to hide <matplotlib.lines.Line2D> in IPython notebook?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 542 Views

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]: []

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Embedding small plots inside subplots in Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 5K+ Views

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, ...

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How to change the figuresize using Seaborn factorplot in Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 433 Views

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

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How to set the font size of Matplotlib axis Legend?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 2K+ Views

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)") ...

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Show the origin axis (x,y) in Matplotlib plot

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 09-Apr-2021 13K+ Views

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", ...

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