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Matplotlib Articles
Page 30 of 91
How to change the separation between tick labels and axis labels in Matplotlib?
To change the separation between tick labels and axis labels in Matplotlib, we can use labelpad in xlabel() method.StepsSet the figure size and adjust the padding between and around the subplots.Plot data points of a list using plot() method.Set the ticks on the axes.Set X and Y axes margins to 0.Set the X-axis label with labelpad.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 plt.plot([1, 2, 3, 4, 5]) plt.xticks([1, 2, 3, 4, 5]) plt.margins(x=0, y=0) plt.xlabel("X-axis", labelpad=7) plt.show()Output
Read MoreHow to modify the font size in Matplotlib-venn?
To modify the font size in Matplotlib-venn, we can use set_fontsize() method.StepsSet the figure size and adjust the padding between and around the subplots.Create three sets for Venn diagram.Plot a 3-set area-weighted Venn diagram.To set the set_labels and subset_labels fontsize, we can use set_fontsize() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt from matplotlib_venn import venn3 plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True set1 = {'a', 'b', 'c', 'd'} set2 = {'a', 'b', 'e'} set3 = {'a', 'd', 'f'} out = venn3([set1, set2, set3], ('Set1', 'Set2', 'Set3')) for text in out.set_labels: ...
Read MoreHow to plot a non-square Seaborn jointplot or JointGrid? (Matplotlib)
To plot a non-square Seaborn jointplot or jointgrid, we can use set_figwidth() and set_figheight() methods.StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Create a dataframe with two columns.Use jointplot() method to plot the jointplot.To make it non-square, we can set the figure width and height.To display the figure, use show() method.Exampleimport seaborn as sns import numpy as np from matplotlib import pyplot as plt import pandas as pd 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 ...
Read MoreHow to add a legend on Seaborn facetgrid bar plot using Matplotlib?
StepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe with col1 columns.Multi-plot grid for plotting conditional relationships.Use map_dataframe(). This method is suitable for plotting with functions that accept a long-form DataFrame as a 'data' keyword argument and access the data in that DataFrame using string variable names.Add a legend to the plot().To display the figure, use show() method.Exampleimport pandas as pd import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'col1': [3, 7, 8]}) g = sns.FacetGrid(df, col="col1", hue="col1") g.map_dataframe(sns.scatterplot) g.set_axis_labels("X", ...
Read MoreHow to retrieve the list of supported file formats for Matplotlib savefig()function?
To retrieve the list of supported file formats for matplotlib savefig() function, we can use get_supported_filetypes().StepsFirst get the current figure.Set the canvas that contains the figure.Use get_supported_filetypes() method.Iterate the file type items.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt fs = plt.gcf().canvas.get_supported_filetypes() for key, val in fs.items(): print(key, ":", val)Outputeps : Encapsulated Postscript jpg : Joint Photographic Experts Group jpeg : Joint Photographic Experts Group pdf : Portable Document Format pgf : PGF code for LaTeX png : Portable Network Graphics ps : Postscript raw : Raw RGBA bitmap rgba : Raw RGBA bitmap ...
Read MoreHow to make an arrow that loops in Matplotlib?
To make an arrow that loops in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.To make an arrow loop in matplotlib, we can use make_loop() method.Make a wedge instance with center, radius, theta1, theta2 and width.To put the arrow top of the loop, use PathCollection.Add patch collection to the current axes.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt, patches, collections plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True def make_loop(center, radius, theta1=-30, theta2=180): rwidth = 0.02 ring = patches.Wedge(center, radius, theta1, ...
Read MoreHow to change the datetime tick label frequency for Matplotlib plots?
To change the datetime tick label frequency for Matplotlib plots, we can create a dataframe and plot them in some date rangeStepsSet the figure size and adjust the padding between and around the subplots.To make potentially heterogeneous tabular data, use Pandas dataframe.Plot the dataframe using plot() method.Set X-axis major locator, i.e., ticks.Set X-axis major formatter, i.e., tick labels.Use autofmt_xdate(). Date ticklabels often overlap, so it is useful to rotate them and right align them.To display the figure, use show() method.Exampleimport pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib.dates as mdates plt.rcParams["figure.figsize"] = [7.50, ...
Read MoreHow to add a legend to a Matplotlib pie chart?
To add a legend to a Matplotlib pie chart, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of labels, colors, and sizes.Use pie() method to get patches and texts with colors and sizes.Place a legend on the plot with patches and labels.Set equal scaling (i.e., make circles circular) by changing the axis limits.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 labels = ['Walk', 'Talk', 'Sleep', 'Work'] sizes = [23, 45, 12, 20] colors = ['red', 'blue', ...
Read MoreHow to make more than 10 subplots in a figure using Matplotlib?
To make more than 10 subplots in a figure, we can use subplots() method with some rows and columns.StepsSet the figure size and adjust the padding between and around the subplots.Initialize rows count and columns count.Create a figure and a set of subplots with rows☓cols subplots.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 rows = 4 cols = 3 fig, axes = plt.subplots(nrows=rows, ncols=cols) plt.show()Output
Read MoreHow to plot a jointplot with 'hue' parameter in Seaborn? (Matplotlib)
To plot a jointplot with hue parameter in Seaborn, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create x data points using numpy.Make a dictionary with some curve data.Make a dataframe for tabular data.Make a jointplot using jointplot() method.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import pandas as pd import seaborn as sns import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(0, 1, 5) d = { 'y=sin(x)': np.sin(x), 'y=cos(x)': np.cos(x), ...
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