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Matplotlib Articles
Page 28 of 91
How to change the linewidth and markersize separately in a factorplot in Matplotlib?
To change the linewidth and markersize separately in a factorplot, we can use the following steps −Set the figure size and adjust the padding between and around the subplots.Load an example dataset from the online repository.Use factorplot() method with scale to change the marker size.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 exercise = sns.load_dataset("exercise") g = sns.factorplot(x="time", y="pulse", hue="kind", data=exercise, ci=95, markers=['o', '*', 'd'], ...
Read MoreHow to change the space between bars when drawing multiple barplots in Pandas? (Matplotlib)
To change the space between bars when drawing multiple barplots in Pandas within a group, we can use linewidth in plot() method.StepsSet the figure size and adjust the padding between and around the subplots.Make a dictionary with two columns.Create a two-dimensional, size-mutable, potentially heterogeneous tabular data.Plot the dataframe with plot() method, with linewidth that change the space between the bars.Place a legend on the plot.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 d = {'Column 1': [i for i in range(10)], ...
Read MoreHow to install Matplotlib without installing Qt using Conda on Windows?
To install Matplotlib package with Conda, run one of the following −conda install -c conda-forge matplotlib-base conda install -c conda-forge/label/testing matplotlib-base conda install -c conda-forge/label/testing/gcc7 matplotlib-base conda install -c conda-forge/label/cf202003 matplotlib-base conda install -c conda-forge/label/matplotlib_rc matplotlib-base conda install -c conda-forge/label/gcc7 matplotlib-base conda install -c conda-forge/label/broken matplotlib-base conda install -c conda-forge/label/matplotlib-base_rc matplotlib-base conda install -c conda-forge/label/rc matplotlib-base conda install -c conda-forge/label/cf201901 matplotlib-base
Read MoreHow to reuse plots in Matplotlib?
To reuse plots 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 figure using figure() method.Plot a line with some input lists.To reuse the plot, update y data and the linewidth of the plotTo 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 line, = plt.plot([1, 3], [3, 4], label="line plot", color='red', lw=0.5) line.set_ydata([3.5]) line.set_linewidth(4) plt.show()Output
Read MoreHow to modify a Matplotlib legend after it has been created?
To modify a Matplotlib legend after it has been created, we can have multiple methods to modify the created legend.Set the figure size and adjust the padding between and around the subplots.Plot a line using plot() method, with two lists and a label.Use legend() method to place a legend over the plot.To modify the matplotlib legend, use set_title() method.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, 3, 4, 5, 2, 1], [3, 4, 1, 3, 0, 1], label="line plot", color='red', lw=0.5) ...
Read MorePlotting error bars from a dataframe using Seaborn FacetGrid (Matplotlib)
To plot error bars from a dataframe using Seaborn FacetGrid, we can use following steps −Get a two-dimensional, size-mutable, potentially heterogeneous tabular data.Multi-plot grid for plotting conditional relationships.Apply a plotting function to each facet's subset of the data.To display the figure, use show() method.Exampleimport pandas as pd import seaborn as sns from matplotlib import pyplot as plt df = pd.DataFrame({'col1': [3.0, 7.0, 8.0], 'col2': [1.0, 4.0, 3.0]}) g = sns.FacetGrid(df, col="col1", hue="col1") g.map(plt.errorbar, "col1", "col2", yerr=0.75, fmt='o') plt.show()Output
Read MoreHow can I get pyplot images to show on a console app? (Matplotlib)
To show pyplot images on a console, we can use pyplot.show() method.StepsSet the figure size and adjust the padding between and around the subplots.Create random data of 5☓5 dimension.Use imshow() method, with data. Display the data as 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 plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(5, 5) plt.imshow(data, cmap="copper") plt.show()Output
Read MoreHow to produce a barcode in Matplotlib?
To produce a barcode in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a list of binary numbers, i.e., 0s and 1s.Create a new figure or activate an existing figure with dpi=100Add an axes to the figure.Turn off the axes.Use imshow() method to plot the data from step 2.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 code = np.array([ 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, ...
Read MoreHow to handle times with a time zone in Matplotlib?
To handle times with a time zone in Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a dataframe, i.e., two-dimensional, size-mutable, potentially heterogeneous tabular data.To handle times with a time zone, use pytz library that brings the Olson tz database into Python. This library allows accurate and cross-platform timezone calculations.Plot the dataframe using plot() method.To display the figure, use show() method.Exampleimport pandas as pd import numpy as np from matplotlib import pyplot as plt import pytz plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame( ...
Read MoreHow to change the default path for "save the figure" in Matplotlib?
To change the default path for "save the figure", we can use rcParams["savefig.directory"] to set the directory path.StepsSet the figure size and adjust the padding between and around the subplots.Create random data using numpy.Use imshow() method. Display the data as an image, i.e., on a 2D regular raster.Save the figure using plt.savefig() method.Exampleimport os import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True dir_name = "C:/Windows/Temp/" plt.rcParams["savefig.directory"] = os.chdir(os.path.dirname(dir_name)) data = np.random.rand(5, 5) plt.imshow(data, cmap="copper") plt.savefig("img.png")OutputWhen we execute the code, it will save the following plot as ...
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