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Articles by Rishikesh Kumar Rishi
Page 50 of 102
Colouring the edges by weight in networkx (Matplotlib)
To color the edges by weight in networkx, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a graph with edges, name, or graph attributes.Add nodes to the current graph.Add edges to the current graph's nodes.Iterate the given graph's edges and set some weight to them.Draw current graphs with weights for edge color.To display the figure, use show() method.Exampleimport random as rd import matplotlib.pylab as plt import networkx as nx plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True G = nx.DiGraph() G.add_nodes_from([1, 2, 3, 4]) G.add_edges_from([(1, 2), (2, 3), ...
Read MorePlotting animated quivers in Python using Matplotlib
To animate quivers in Python, 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.Create u and v data points using numpy.Create a figure and a set of subplots.Plot a 2D field of arrows using quiver() method.To animate the quiver, we can change the u and v values, in animate() method. Update the u and v values and the color of the vectors.To display the figure, use show() method.Exampleimport numpy as np import random as rd from matplotlib import pyplot as plt, animation ...
Read MoreHow to make markers on lines smaller in Matplotlib?
To make markers on lines smaller in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create random data points, x.Plot x data points using plot() method, with linewidth =0.5 and color="black".To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.rand(20) plt.plot(x, '*-', color='black', markersize=10, lw=0.5) plt.show()Output
Read MoreHow can I make Matplotlib.pyplot stop forcing the style of my markers?
To make matplotlib.pyplot stop forcing the style of markers, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create random x and y data points using numpy.Plot x and y data points using plot() method, with "r*" marker with markersize=10.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.random.rand(20) y = np.random.rand(20) plt.plot(x, y, 'r*', markersize=10) plt.show()Output
Read MoreSetting the limits on a colorbar of a contour plot in Matplotlib
To set the limits on a colorbar of a countour plot in Matplotlib, 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.Get the data using x and y.Get the coordinate matrices from the coordinate vectors.Initialize vmin and vmax to set the limits on a colorbar of a contour plot in matplotlib.Plot contours using contourf() method.Make the colorbar using scalar mappable within the range of vmin and vmax.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import numpy as np from ...
Read MoreHow can I make the xtick labels of a plot be simple drawings using Matplotlib?
To make xtick labels of a plot be simple drawings using Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize the y position of simple drawings.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 using add_subplot()method.Plot a line using plot() method.Set the X-axis ticks using set_ticks() method.Set empty tick labels.Add circles and rectangles patches using add_patch() method. Instantiate Circle() and Rectangle() class.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import matplotlib.patches as patches ...
Read MoreIndicating the statistically significant difference in bar graph (Matplotlib)
To indicate the statistically significant difference in bar graph, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create means, std, index, width and labels data points.Create a figure and a set of subplots using subplots() method.Make a bar plot using bar() method.Plot Y versus X as lines and/or markers with attached errorbars.Scale the Y-axis.Get or set the current tick locations and labels of the X-axis.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 = (5, 15, ...
Read MoreHow to show node name in Matplotlib graphs using networkx?
To show node name in graphs using networkx, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Initialize a graph with edges, name, or graph attributes.Add multiple nodes using add_nodes_from() method.Add all the edges using add_edge_from() method.Draw the graph G with Matplotlib using draw() method. Set with_labels to True.To display the graph, we can use show() method.Exampleimport matplotlib.pylab as plt import networkx as nx plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True G = nx.DiGraph() G.add_nodes_from([1, 2, 3, 4]) G.add_edges_from([(1, 2), (2, 1), (2, 3), (1, 4), (3, 4)]) nx.draw(G, ...
Read MoreHow to add a title on Seaborn lmplot?
To add a title on Seaborn Implot, we can take the following steps−Set the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe with two columns, X-Axis and Y-AxisUse implot() method.Get the current axis using gca() method.To display the figure, use show() method.Exampleimport pandas import matplotlib.pylab as plt import seaborn as sns import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pandas.DataFrame({"X-Axis": [np.random.randint(10) for i in range(10)], "Y-Axis": [i for i in range(10)]}) bar_plot = sns.lmplot(x='X-Axis', y='Y-Axis', data=df, height=3.5) ax = plt.gca() ax.set_title("Random Data Implot") ...
Read MoreTransparency for Poly3DCollection plot in Matplotlib
To plot a transparent Poly3DCollection plot in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplotsCreate a new figure or activate an existing figure.Add an '~.axes.Axes' to the figure as part of a subplot arrangement with projection=3d.Create x, y and z data points.Make a list of vertices.Convert x, y and z data points into a zipped list of tuples.Get a list of instance of Poly3d.Add a 3D collection object to the plot using add_collection3d() method.Turn off the axes.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt ...
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