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Articles by Rishikesh Kumar Rishi
Page 100 of 102
Change x axes scale in matplotlib
Using plt.xticks, we can change the X-axis scale.StepsUsing plt.plot() method, we can create a line with two lists that are passed in its argument.Add text to the axes. Add the text *s* to the axes at location *x*, *y* in data coordinates, using plt.text() method, where the font size can be customized by changing the font-size value.Using xticks method, get or set the current tick locations and labels of the X-axis.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.plot([1, 2, 4], [1, 2, 4]) plt.text(2, 3, "y=x", color='red', fontsize=20) plt.xticks([1, 2, 3, 4, 5]) ...
Read MorePython matplotlib multiple bars
We can use a user-defined method, autolabel, to annotate the axis value. Before that, we can initialize the fig and ax using plt.subplots() method.StepsCreate lists, labels, men_means, and women_means with different data elements.Return evenly spaced values within a given interval, using numpy.arrange() method.Set the width variable i.e., width=0.35.Create fig and ax variables using subplots method, where default nrows and ncols are 1.The bars are positioned at *x* with the given *align*\ment. Their dimensions are given by *height* and *width*. The vertical baseline is *bottom* (default 0), so create rect1 and rect2 using plt.bar() method.Set the Y-axis label using plt.ylabel() method.Set ...
Read MoreGetting vertical gridlines to appear in line plot in matplotlib
Using plt.grid(axis="x") method, we can plot vertical gridlines.StepsMake a list of numbers.Set the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Toggle the gridlines, and optionally set the properties of the lines, using plt.grid() method.To show the figure, use the plt.show() method, where the argument axis can be “x”, “y” or “both”.Examplefrom matplotlib import pyplot as plt plt.plot([0, 5], [0, 5]) plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.grid(axis="x") plt.show()Output
Read MoreHow to plot a high resolution graph in Matplotlib?
We can use the resolution value, i.e., dots per inch, and the image format to plot a high-resolution graph in Matplotlib.StepsCreate a dictionary with Column 1 and Column 2 as the keys and Values are like i and i*i, where i is from 0 to 10, respectively.Create a data frame using pd.DataFrame(d); d created in step 1.Plot the data frame with ‘o’ and ‘rx’ style.To save the file in pdf format, use savefig() method where the image name is myImagePDF.pdf, format="pdf".We can set the dpi value to get a high-quality image.Using the saving() method, we can save the image with ...
Read MoreHow do I get interactive plots again in Spyder/Ipython/matplotlib?
To get interactive plots, we need to activate the figure. Using plt.ioff() and plt.ion(), we can perform interactive actions with plot.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Draw a line, using plot() method.Set the color of the line, i.e., orange.Stopped the interaction, using plt.ioff() method.To make the interaction plots, change the color of the line coordinate.Start the interaction, using plt.ion() method.ExampleTo use interactive plot in Ipython -In [1]: %matplotlib auto Using matplotlib backend: GTK3Agg In [2]: import matplotlib.pyplot as plt In [3]: fig, ax = plt.subplots() # Diagram will ...
Read MoreHow to plot two columns of a Pandas data frame using points?
First, we can initialize the dictionary with col1 and col2, convert it into a data frame. After that, we can plot this data with ‘o’ and ‘rx’ style.StepsCreate a dictionary with Column 1 and Column 2 as the keys and Values are like i and i*i, where i is from 0 to 10, respectively.Create a data frame using pd.DataFrame(d); d created in step 1.Plot the data frame with ‘o’ and ‘rx’ style.To show the plot, use plt.show().Exampleimport pandas as pd from matplotlib import pyplot as plt d = {'Column 1': [i for i in range(10)], 'Column 2': [i*i for ...
Read MoreHow do you determine which backend is being used by matplotlib?
Using matplotlib.get_backend(), we can get the backend value.StepsImport matplotlib.To return the name of the current backend, use the get_backend() method.Exampleimport matplotlib print("Backend used by matplotlib is: ", matplotlib.get_backend())OutputBackend used by matplotlib is: GTK3Agg
Read MoreHow to dynamically update a plot in a loop in Ipython notebook?
We can iterate a plot using display.clear_output(wait=True), display.display(pl.gcf()) and time.sleep() methods in a loop to get the exact output.StepsPlot a sample (or samples) from the "standard normal" distribution using pylab.randn().Clear the output of the current cell receiving output, wait=False(default value), wait to clear the output until new output is available to replace it.Display a Python object in all frontends. By default, all representations will be computed and sent to the frontends. Frontends can decide which representation is used and how, using the display() method. pl.gcf helps to get the current figure.To sleep for a while, use time.sleep() method.Exampleimport time import ...
Read MoreCreating a Heatmap in matplotlib with pcolor
First, we can create an image using imshow method, taking a harvest matrix. After that, we can mark those image pixels with some value.StepsCreate a list of subjects.Create a list of students.Create a harvest matrix.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Display data as an image, i.e., on a 2D regular raster, with step 1 data.Get or set the current tick locations and labels of the X-axis, with the length of students.Get or set the current tick locations and labels of the Y-axis, with the length of subjects.Set X-axis tick labels of the ...
Read MoreHow can I plot a confusion matrix in matplotlib?
Using imshow method, we can create an image with an input (5, 5) array dimension. After that, we can use the xticks and yticks method to mark the ticks on the axes.StepsReturn random floats in the half-open interval [5, 5) and interpolation='nearest'.Display data as an image, i.e., on a 2D regular raster, with step 1 data.Get or set the current tick locations and labels of the X-axis, using xticks method.Get or set the current tick locations and labels of the Y-axis, using yticks method.Use plt.show() to show the figure.Exampleimport matplotlib.pyplot as plt import numpy as np plt.imshow(np.random.random((5, 5)), interpolation='nearest') ...
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