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Python Articles
Page 531 of 852
How to set Dataframe Column value as X-axis labels in Python Pandas?
To set Dataframe column value as X-axis labels in Python Pandas, we can use xticks in the argument of plot() method.StepsSet the figure size and adjust the padding between and around the subplots.Make a dataframe using Pandas with column1 key.Plot the Pandas dataframe using plot() method with column1 as the X-axis column.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 data = pd.DataFrame({"column1": [4, 6, 7, 1, 8]}) data.plot(xticks=data.column1) plt.show()Output
Read MorePlot a polar color wheel based on a colormap using Python/Matplotlib
To plot a color wheel based on a colormap using Python/Matplotlib, we can use the colorbar class and can use copper colormap.StepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the figure using add_axes() method.Set the direction of the axes.Linearly normalize the data using Normalize class.Draw a colorbar in an existing axes.Set the artist's visibility.Turn the X- and Y-axis off.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, cm, colors, colorbar plt.rcParams["figure.figsize"] = [7.50, 3.50] ...
Read MoreConnecting two points on a 3D scatter plot in Python and Matplotlib
To connect two points on a 3D scatter plot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an axes to the current figure as a subplot arrangement.Create lists for x, y and z.Plot x, y and z data points using scatter() methodTo connect the points, use plot() method with x, y and z data points with black color line.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 fig = ...
Read MoreHow to plot statsmodels linear regression (OLS) cleanly in Matplotlib?
We can plot statsmodels linear regression (OLS) with a non-linear curve but with linear data.StepsSet the figure size and adjust the padding between and around the subplots.To create a new one, we can use seed() method.Initialize the number of sample and sigma variables.Create linear data points x, X, beta, t_true, y and res using numpy.Res is an ordinary Least Square class instance.Calculate the standard deviation. Confidence interval for prediction applies to WLS and OLS, not to general GLS, that is, independently but not identically distributed observations.Create a figure and a set of subplots using subplot() method.Plot all the curves using ...
Read MoreControlling the alpha value on a 3D scatter plot using Python and Matplotlib
To control the alpha value on a 3D scatter plot using Python and Matplotlib, we can set the facecolor and edgecolors value.Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure using figure() method.Add an '~.axes.Axes' to the figure as part of a subplot arrangement.Create x, y and z data points using numpy.Plot x, y and z points using scatter() method.Set the facecolors and edgecolors.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 = plt.figure() ax ...
Read MoreHow to make Matplotlib show all X coordinates?
To show all X coordinates (or Y coordinates), we can use xticks() method (or yticks()).StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Set x=0 and y=0 margins on the axes.Plot x and y data points using plot() method.Use xticks() method to show all the X-coordinates in the plot.Use yticks() method to show all the Y-coordinates in 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] plt.rcParams["figure.autolayout"] = True x = np.arange(0, 10, 1) y =np.arange(0, 10, 1) plt.margins(x=0, y=0) ...
Read MoreHow to customize the axis label in a Seaborn jointplot using Matplotlib?
To customize the axis label in a Seaborn jointplot, we can take the following stepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Use jointplot() method to plot a joint plot in Seaborn.To set the customized axis label, we can use LaTex representation or set_xlabel() method properties.To display the figure, use show() method.Exampleimport seaborn as sns import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.randn(1000, ) y = 0.2 * np.random.randn(1000) + 0.5 h = sns.jointplot(x, y, height=3.50) h.ax_joint.set_xlabel('$\bf{X-Axis\ ...
Read MoreHow to decrease the density of x-ticks in Seaborn?
To decrease the density of x-ticks in Seaborn, we can use set_visible=False for odd positions.StepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe with X-axis and Y-axis keys.Show the point estimates and confidence intervals with bars, using barplot() method.Iterate bar_plot.get_xticklabels() method. If index is even, then make them visible; else, not visible.To display the figure, use show() method.Exampleimport pandas import matplotlib.pylab as plt import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pandas.DataFrame({"X-Axis": [i for i in range(10)], "Y-Axis": [i for i in range(10)]}) bar_plot = sns.barplot(x='X-Axis', y='Y-Axis', data=df) for ...
Read MoreHow to remove the space between subplots in Matplotlib.pyplot?
To remove the space between subplots in matplotlib, we can use GridSpec(3, 3) class and add axes as a subplot arrangement.StepsSet the figure size and adjust the padding between and around the subplots.Add a grid layout to place subplots within a figure.Update the subplot parameters of the gridIterate in the range of dimension of grid specs.Add a subplot to the current figure.Set the aspect ratios.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import matplotlib.gridspec as gridspec plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True gs1 = gridspec.GridSpec(3, 3) gs1.update(wspace=0.5, hspace=0.1) for i in range(9): ax1 = plt.subplot(gs1[i]) ax1.set_aspect('equal') plt.show()Output
Read MoreWhat is the difference between plt.show and cv2.imshow in Matplotlib?
A simple call to the imread method loads our image as a multi-dimensional NumPy array (one for each Red, Green, and Blue component, respectively) and imshow displays our image on the screen. Whereas, cv2 represents RGB images as multi-dimensional NumPy arrays, but in reverse order.StepsSet the figure size and adjust the padding between and around the subplots.Initialize the filename.Add a subplot to the current figure using nrows=1, ncols=2, and index=1.Read the image using cv2.Off the axes and show the figure in the next statement.Add a subplot to the current figure using nrows=1, ncols=2, and index=2.Read the image using plt.Off the ...
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