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Matplotlib Articles
Page 45 of 91
How to plot gamma distribution with alpha and beta parameters in Python using Matplotlib?
To plot gamma distribution with alpha and beta parameters in Python, we can use gamma.pdf() function.StepsSet the figure size and adjust the padding between and around the subplots.Create x using numpy and y using gamma.pdf() function at x of the given RV.Plot x and y data points using plot() method.Use legend() method to place the legend elements for the plot.To display the figure, use show() method.Exampleimport numpy as np import scipy.stats as stats from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(0, 10, 10) y = stats.gamma.pdf(x, a=5, scale=0.333) plt.plot(x, ...
Read MoreHow to change the font size of scientific notation in Matplotlib?
To change the fontsize of scientific notation 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 x and y values.Plot x and y data points using plot() method.To change the font size of scientific notation, we can use style="sci" class by name.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 x = [10000, 20000, 300000, 34, 1, 10000] y = [1, 2, 0, 4, 1, 5] plt.plot(x, y, color='red') plt.ticklabel_format(axis="x", style="sci", scilimits=(0, ...
Read MoreHow do I plot hatched bars using Pandas and Matplotlib?
To plot hatches bars using Pandas, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a dataframe using Pandas with two columns.Add an axes to the current figure as a subplot arrangement.Make a plot with kind="bars" class by name.Make a list of hatches.Get the bars patches using bars.patches.Iterate bars patches and set the hatch of each patch.To display the figure, use show() method.Exampleimport numpy as np import pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(np.random.rand(5, 2), columns=['a', ...
Read MoreHow to show different colors for points and line in a Seaborn regplot?
To show different colors for points and line in a Seaborn regplot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe with key X-axis and Y-axis.Plot numeric independent variables with regression model.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(5) for i in range(10)], "Y-Axis": [np.random.randint(5) for i in range(10)]}) sns.regplot(x='X-Axis', y='Y-Axis', data=df, scatter_kws={"color": "red"}, line_kws={"color": "green"}) plt.show()Output
Read MoreHow can I render 3D histograms in Python using Matplotlib?
To render 3D histograms in Python, 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.Add an axes to the cureent figure as a subplot arrangement.Create x3, y3 and z3 data points using numpy.Create dx, dy and dz data points using numpy.Use bar3d() method to plot 3D bars.To hide the axes use axis('off') class by name.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 ...
Read MoreAdding a legend to a Matplotlib boxplot with multiple plots on the same axis
To add a legend to a matplotlib boxplot with multiple plots on the same axis, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create random data, a and b, using numpy.Create a new figure or activate an existing figure using figure() method.Add an axes to the current figure as a subplot arrangement.Make a box and whisker plot using boxplot() method with different facecolors.To place the legend, use legend() method with two boxplots, bp1 and bp2, and ordered label for legend elements.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt ...
Read MoreHow to draw an average line for a scatter plot in MatPlotLib?
To draw an average line for a plot in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Make x and y data points using numpy.Use subplots() method to create a figure and a set of subplots.Use plot() method for x and y data points.Find the average value of the array, x.Plot x and y_avg data points using plot() method.Place a legend on the figure.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 x ...
Read MoreHow to remove X or Y labels from a Seaborn heatmap?
To remove X or Y labels from a Seaborn heatmap, we can use yticklabel=False.StepsSet the figure size and adjust the padding between and around the subplots.Make a Pandas dataframe with 5 columns.Use heatmap() method to plot rectangular data as a color-encoded matrix with yticklabels=False.To display the figure, use show() method.Exampleimport seaborn as sns import pandas as pd import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame(np.random.random((5, 5)), columns=["col1", "col2", "col3", "col4", "col5"]) sns.heatmap(df, yticklabels=False) plt.show()Output
Read MoreBest way to display Seaborn/Matplotlib plots with a dark iPython Notebook profile
To display a Seaborn/Matplolib plot with a dark background, we can use "dark" in set_style() method that gives an aesthetic style to the plots.StepsSet the figure size and adjust the padding between and around the subplots.Use "dark" in set_style() method that sets the aesthetic style.Create a Pandas dataframe with two columns.Show point estimates and confidence intervals with bars, using bar plot() method.Rotate xticks by 45 degrees.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 sns.set_style("dark") df = pandas.DataFrame({"X-Axis": [np.random.randint(10) ...
Read MoreAutomatic detection of display availability with Matplotlib
To detect display availability with matplotlib, we can take the following steps −StpsImport os module.Use os.environ["DISPLAY"] to get the available display.Exampleimport os env = os.environ["DISPLAY"] print("Automatic detected display availability: ", env)OutputAutomatic detected display availability: 0
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