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Matplotlib Articles
Page 63 of 91
How to switch axes in Matplotlib?
To switch axes in matplotlib, we can create a figure and add two subplots using subplots() method. Plot curves, extract x and y data, and set these data in a second plotted curve.StepsCreate x and y data points using numpy.Create a figure and add a set of two subplots.Set the title of the plot on both the axes.Plot x and y data points using plot() method.Extract the x and y data points using get_xdata and get_ydata.To switch the axes of the plot, set x_data and y_data of the axis 1 curve to axis 2 curve.Adjust the padding between and around the subplots.To display the ...
Read MorePlace text inside a circle in Matplotlib
To place text inside a circle in matplotlib, we can take the following steps −Create a new figure or activate an existing figure using figure() method.Add a subplot method to the current axis.Create a Circle instance using Circle() class.Add a circle path on the plot.To place the text in the circle, we can use text() method.Scale x and y axes using xlim() and ylim() methods.To display the figure, use show() method.Exampleimport matplotlib from matplotlib import pyplot as plt, patches plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111) circle = matplotlib.patches.Circle((0, 0), radius=1, color='yellow') ax.add_patch(circle) plt.text(-.25, 0, "This is a Circle") plt.xlim([-4, 4]) plt.ylim([-4, 4]) plt.axis('equal') ...
Read MoreHow to reshape a networkx graph in Python?
To reshape a networkx graph in Python, we can take the following steps −Create a data frame using Panda's data frame.Return a graph from Pandas DataFrame containing an edge list using from_pandas_edgelist() method.Draw the graph G with matplotlib. We can reshape the network by increasing and decreasing the list of keys "from" and "to".To display the figure, use show() method.Exampleimport pandas as pd import networkx as nx from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'from': ['A', 'B', 'C', 'A'], 'to': ['D', 'A', 'E', 'C']}) G = nx.from_pandas_edgelist(df, 'from', 'to') nx.draw(G, with_labels=True, node_size=150, alpha=0.5, linewidths=40) plt.show()Output
Read MoreHow to display print statements interlaced with Matplotlib plots inline in iPython?
To display print statements interlaced with matplotlib plots inline in iPython, we can take the following steps.StepsImport pyplot from matplotlib.Make a list of data for hist plots.Initialize a variable "i" to use in print statement.Iterate the list of data (Step 2).Create a figure and a set of subplots using subplots() method.Place print statement.Plot the histogram using hist() method.Increase "i" by 1.ExampleIn [1]: from matplotlib import pyplot as plt In [2]: myData = [[7, 8, 1], [2, 5, 2]] In [3]: i = 0 In [4]: for data in myData: ...: fig, ax = plt.subplots() ...: print("data number i =", ...
Read MoreHow to remove relative shift in Matplotlib axis?
To remove relative shift in matplotlib axis, we can take the following steps −Plot a line with two input lists.Using gca() method, get the current axis and then return the X-axis instance. Get the formatter of the major ticker. To remove the relative shift, use set_useOffset(False) method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True plt.plot([10, 101, 1001], [1, 2, 3]) plt.gca().get_xaxis().get_major_formatter().set_useOffset(False) plt.show()Output
Read MoreDefine the size of a grid on a plot using Matplotlib
To define the size of a grid on a plot, we can take the following steps −Create a new figure or activate an existing figure using figure() method.Add an axes to the figure as a part of a subplot arrangement.Plot a curve with an input list.Make x and y margins 0.To set X-grids, we can pass input ticks points.To lay out the grid lines in current line style, use grid(True) method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(111) ax.plot([0, 2, 5, 8, 10, 1, 3, 14], ...
Read MoreHow to adjust the space between legend markers and labels in Matplotlib?
To adjust the space between legend markers and labels, we can use labelspacing in legend method.StepsPlot lines with label1, label2 and label3.Initialize a space variable to increase or decrease the space between legend markers and label.Use legend method with labelspacing in the arguments.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True plt.plot([0, 1], [0, 1.0], label='Label 1') plt.plot([0, 1], [0, 1.1], label='Label 2') plt.plot([0, 1], [0, 1.2], label='Label 3') space = 2 plt.legend(labelspacing=space) plt.show()Output
Read MoreHow to redefine a color for a specific value in a Matplotlib colormap?
To redefine a color for a specific value in matplotlib colormap, we can take the following steps −Get a colormap instance, defaulting to rc values if *name* is None using get_cmap() method, with gray colormap.Set the color for low out-of-range values when "norm.clip = False" using set_under() method.Using imshow() method, display data an image, i.e., on a 2D regular raster.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt, cm plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True cmap = cm.get_cmap('gray') cmap.set_under('red') plt.imshow(np.arange(25).reshape(5, 5), interpolation='none', cmap=cmap, vmin=.001) plt.show()Output
Read MoreAnimate a rotating 3D graph in Matplotlib
To make a rotating 3D graph in matplotlib, we can use Animation class for calling a function repeatedly.StepsInitialize variables for number of mesh grids, frequency per second to call a function, frame numbers.Create x, y, and z array for a curve.Make a function to make z array using lambda function.To pass a function into the animation class, make a user-defined function to remove the previous plot and plot a surface using x, y, and zarray.Create a new figure or activate an existing figure.Add a subplot arrangement using subplots() method.Set the Z-axis limit using set_zlim() method.Call the animation class to animate the surface plot.To display ...
Read MoreHow to plot two Seaborn lmplots side-by-side (Matplotlib)?
To plot two graphs side-by-side in Seaborn, we can take the following steps −To create two graphs, we can use nrows=1, ncols=2 with figure size (7, 7).Create a data frame with keys, col1 and col2, using Pandas.Use countplot() to show the counts of observations in each categorical bin using bars.Adjust the padding between and around the subplots.To display the figure, use show() method.Exampleimport pandas as pd import numpy as np import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True f, axes = plt.subplots(1, 2) df = pd.DataFrame(dict(col1=np.linspace(1, 10, 5), col2=np.linspace(1, 10, 5))) sns.countplot(df.col1, x='col1', ...
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