Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.bxp() Function
The Axes.bxp() function in axes module of matplotlib library is used to make a box and whisker plot for each column of x or each vector in sequence x.
Syntax: Axes.bxp(self, bxpstats, positions=None, widths=None, vert=True, patch_artist=False, shownotches=False, showmeans=False, showcaps=True, showbox=True, showfliers=True, boxprops=None, whiskerprops=None, flierprops=None, medianprops=None, capprops=None, meanprops=None, meanline=False, manage_ticks=True, zorder=None)
Parameters: This method accept the following parameters that are described below:
- bxpstats : This parameter is alist of dictionaries containing stats for each boxplot.
- positions : This parameter is used to sets the positions of the violins.
- vert: This parameter is an optional parameter and contain boolean value. It makes the vertical violin plot if true.Otherwise horizontal.
- widths: This parameter is used to sets the width of each violin either with a scalar or a sequence.
- patch_artist : This parameter is used to produce boxes with the Line2D artist if it is false. Otherwise, boxes with Patch artists.
- manage_ticks : This parameter is used to adjust the tick locations and labels.
- zorder : This parameter is used to sets the zorder of the boxplot.
- shownotches: This parameter contain boolean value. It is used to produce a notched and rectangular box plot.
- showmeans : This parameter contain boolean value. It is used to toggle rendering of the means.
- showcaps : This parameter contain boolean value. It is used to toggle rendering of the caps.
- showfliers : This parameter contain boolean value. It is used to toggle rendering of the fliers.
- boxprops : This parameter is used to set the plotting style of the boxes.
- whiskerprops : This parameter is used to set the plotting style of the whiskers.
- capprops : This parameter is used to set the plotting style of the caps.
- flierprops : This parameter is used to set the plotting style of the fliers.
- medianprops : This parameter is used to set the plotting style of the medians.
- meanprops : This parameter is used to set the plotting style of the means.
Returns: This returns the following:
- result :This returns the dictionary which maps each component of the violinplot to a list of the matplotlib.lines.Line2D instances.
Below examples illustrate the matplotlib.axes.Axes.bxp() function in matplotlib.axes:
Example-1:
import numpy as np import matplotlib.pyplot as plt import matplotlib.cbook as cbook np.random.seed(10**7) data = np.random.lognormal(size =(10, 4), mean = 4.5, sigma = 4.75) labels = ['G1', 'G2', 'G3', 'G4'] result = cbook.boxplot_stats(data, labels = labels, bootstrap = 1000) for n in range(len(result)): result[n]['med'] = np.median(data) result[n]['mean'] *= 0.1 fig, axes1 = plt.subplots() axes1.bxp(result) axes1.set_title('matplotlib.axes.Axes.bxp() Example') plt.show() |
Output:
Example-2:
import numpy as np import matplotlib.pyplot as plt import matplotlib.cbook as cbook np.random.seed(10**7) data = np.random.lognormal(size =(37, 4), mean = 4.5, sigma = 1.75) labels = ['G1', 'G2', 'G3', 'G4'] stats = cbook.boxplot_stats(data, labels = labels, bootstrap = 100) for n in range(len(stats)): stats[n]['med'] = np.median(data) stats[n]['mean'] *= 2 fig, [axes1, axes2, axes3] = plt.subplots(nrows = 1, ncols = 3, sharey = True) axes1.bxp(stats) axes2.bxp(stats, showmeans = True) axes3.bxp(stats, showmeans = True, meanline = True) axes2.set_title('matplotlib.axes.Axes.bxp() Example') plt.show() |
Output:
