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Articles by Rishikesh Kumar Rishi
Page 29 of 102
How to get all the legends from a plot in Matplotlib?
To get all the legends from a plot in matplotlib, we can use the get_children() method to get all the properties of an axis, then iterate all the properties. If an item is an instance of a Legend, then get the legend texts.stepsSet the figure size and adjust the padding between and around the subplots.Create x data points using numpy.Create a figure and a set of subplots.Plot sin(x) and cos(x) using plot() method with different labels and colors.Get the children of the axis and get the texts of the legend.To display the figure, use show() method.Exampleimport numpy as np from ...
Read MoreHow to create a Boxplot with Matplotlib?
To create a Boxplot with Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of xticks.Plot a boxplot with xticks data.Set xticks and xtick labels with 45° rotation.To display the figure, use 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 xticks = [1, 4, 5, 2, 3] ax = sns.boxplot(xticks) ax.set_xticks(xticks) ax.set_xticklabels(["one", "two", "three", "four", "five"], rotation=45) plt.show()Output
Read MoreHow to show a bar and line graph on the same plot in Matplotlib?
To show a bar and line graph on the same plot in matplotlib, 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.Create a figure and a set of subplots.Plot the bar and line with the dataframe obtained from Step 2.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 df = pd.DataFrame(dict(data=[2, 4, 1, 5, 9, 6, 0, 7])) fig, ax = plt.subplots() df['data'].plot(kind='bar', color='red') df['data'].plot(kind='line', marker='*', color='black', ms=10) ...
Read MoreHow to plot blurred points in Matplotlib?
To plot blurred points in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing new figure.Add an ax1 to the figure as part of a subplot arrangement.First, we can make a marker, i.e., to be blurred.Set the X and Y axes scale, turn off the axes.Save the marker in a file, and load that image to be plotted after blurred.Close the previous figure, fig1.Create a new figure or activate an existing figure, fig2.Create random data points, x and y.Apply Gaussian filter, to ...
Read MoreHow to add a second X-axis at the bottom of the first one in Matplotlib?
To add a second X-axis at the bottom of the first one in Matplotlib, we can take the followingStepsSet the figure size and adjust the padding between and around the subplots.Get the current axis (ax1) using gca() method.Create a twin axis (ax2) sharing the Y-axis.Set X-axis ticks at AxisSet X-axis labels at Axis 1 andTo display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True ax1 = plt.gca() ax2 = ax1.twiny() ax2.set_xticks([1, 2, 3, 4, 5]) ax1.set_xlabel("X-axis 1") ax2.set_xlabel("X-axis 2") plt.show()Output
Read MoreHow to create a Swarm Plot with Matplotlib?
To create a Swarm Plot with Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe, i.e., a two-dimensional, size-mutable, potentially heterogeneous tabular data.Initialize the plotter, swarmplot.To plot the boxplot, use boxplot() method.To display the figure, use show() method.Exampleimport seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = pd.DataFrame({"Box1": np.arange(10), "Box2": np.arange(10)}) ax = sns.swarmplot(x="Box1", y="Box2", data=data, zorder=0) ...
Read MoreHow to display the matrix value and colormap in Matplotlib?
To display the matrix value and colormap 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 max and min values for matrix.Plot the values of a 2D matrix or array as color-coded image.Iterate each cell of the color-code image and place value at the center.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 fig, ax = plt.subplots() min_val, max_val = 0, 5 matrix = np.random.randint(0, 5, size=(max_val, ...
Read MoreHow to annotate a range of the X-axis in Matplotlib?
To annotate a range of the X-axis in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create xx and yy data points using numpy.Create a figure and a set of subplots.Plot xx and yy data points using plot() method.Set ylim of the axis.Use annotate method to place arrow heads and range tag name.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 xx = np.linspace(0, 10) yy = np.sin(xx) fig, ax = plt.subplots(1, 1) ...
Read MoreHow to annotate several points with one text in Matplotlib?
To add annotated text in Matplotlib for several points, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.To set the label for each scattered point, make a list of labels.Plot xpoints, ypoints using scatter() method. For color, use xpoints.Iterate zipped labels, xpoints and ypoints.Use annotate() method with bold LaTeX representation in a for loop.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 xpoints = np.linspace(1, 10, 10) ...
Read MoreHow to plot a line in Matplotlib with an interval at each data point?
To plot a line in Matplotlib with an interval at each data point, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make an array of means and standard deviations.Plot means using plot() method.Fill the area between means+stds and means-stds, alpha=0.7 and color='yellow'.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 means = np.array([3, 5, 1, 8, 4, 6]) stds = np.array([1.3, 2.6, 0.78, 3.01, 2.32, 2.9]) plt.plot(means, color='red', lw=7) plt.fill_between(range(6), means - stds, means ...
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