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Articles by Rishikesh Kumar Rishi
Page 63 of 102
How to get different font sizes in the same annotation of Matplotlib?
To add different font sizes in the same annotation method, we can take the following stepsMake lists of x and y data points where text could be placed.Initialize a variable 'labels', i.e., a string.Make a list of sizes of the fonts.Use subplots() method to create a figure and a set of subplots.Iterate above lists and annotate each label's text and set its fontsize.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True X = [0.1, .2, .3, .4, .5, .6, 0.8] Y = [0.1, 0.12, 0.13, 0.20, 0.23, 0.25, 0.27] labels = 'Welcome' ...
Read MoreHow to load an image and show the image using Keras?
To load an image and show the image using Keras, we will use load_image() method to load an image and set the target size of the image to be shown.StepsUse load_img() method to load the figure.Set the target size of the image.To display the figure, use show() method.Examplefrom keras.preprocessing import image img = image.load_img('bird.jpg', target_size=(350, 750)) img.show()Output
Read MoreAdjusting the spacing between the edge of the plot and the X-axis in Matplotlib
To adjust the spacing between the edge of the plot and the X-axis, we can use tight_layout() method or set the bottom padding of the current figure.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() 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 x = np.linspace(-2, 2, 100) y = np.exp(x) plt.plot(x, y, c='red', lw=1) plt.show()Output
Read MoreHow to add footnote under the X-axis using Matplotlib?
To add footnote under the X-axis using matplotlib, we can use figtext() and text() method.StepsSet 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 numpy.To place the footnote, use figtext() method with x, y position and box properties.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 x = np.linspace(-2, 2, 100) y = np.exp(x) plt.plot(x, y) plt.figtext(0.5, 0.01, "footnote: $y=e^{x}$", ha="center", fontsize=18, bbox={"facecolor": "green", "alpha": 0.75, "pad": 5}) plt.show()Output
Read MorePlot yscale class linear, log, logit and symlog by name in Matplotlib?
To plot yscale with class by name, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create y data points using numpy.Create x data points using numpy.Add a subplot to the current figure at index 1.Plot x and y data points using plot() method.For linear class by name, use yscale("linear") method.Set the title of the current subplot.Repeat the steps from 4 to 5 with different indices, yscale() class by name, and title of the plot.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] ...
Read MoreHow to locate the median in a (Seaborn) KDE plot?
To locate the median in a seaborn KDE plot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create random data using numpy.Find the median of data (Step 2).Use kdeplot() to plot the shaded region.Use axvline() method to plot the vertical line.To display the figure, use show() method.Exampleimport numpy as np import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.randn(30) xmedian = np.median(data) k = sns.kdeplot(x=data, shade=True) plt.axvline(xmedian, c='red') plt.show()Output
Read MoreHow to set the margins of a Matplotlib figure?
To set the margins of a matplotlib figure, we can use margins() method.StepsSet the figure size and adjust the padding between and around the subplots.Create t and y data points using numpy.Add a subplot to the current figure at index 1.Plot t and y data points using plot() method.Set the title of the plot.Add a subplot to the current figure at index 2.Plot t and y data points using plot() method.Set the title of the plot.Set margins of the plot using margins(x=0, y=0).To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] ...
Read MoreAutomatically setting Y-axis limits for a bar graph using Matplotlib
To set Y-axis limit, we can use ylim() method and put maximum and minimum limit values.StepsSet the figure size and adjust the padding between and around the subplots.Create two lists for data points.Make two variables for max and min values for Y-axis.Use ylim() method to limit the Y-axis range.Use bar() method to plot the bars.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 x = [1, 2, 3, 4, 5] y = [8, 4, 6, 1, 3] max_y_lim = max(y) + .5 min_y_lim = min(y) plt.ylim(min_y_lim, max_y_lim) plt.bar(x, y) ...
Read MoreHow do you improve Matplotlib image quality?
To improve matplotlib image quality we can use greater dot per inch i.e dpi value (greater than 600) and pdf or .eps format can be recommended.StepsSet the figure size and adjust the padding between and around the subplots.Make a 2D data raster using a np.array.Display data as an image, i.e., on a 2D regular raster.Save the current image using savefig() with dpi=1200 and .eps format, 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 data = np.array( [[0.1, 0.7, 0.6, 0.3], ...
Read MoreAnnotate Subplots in a Figure with A, B, C using Matplotlib
To annotate subplots in a figure with A, B and C using matplotlib, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots, with nrows=1 and ncols=3.Make a 1D iterator over an array.Iterate each axes and display data as an image.In the loop itself, place text A, B and C.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt import string plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, axs = plt.subplots(1, 3) axs = axs.flat for index, ax ...
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