Matplotlib.axes.Axes.hist() in Python

13 Apr, 2020
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.
The Axes.hist() function in axes module of matplotlib library is used to plot a histogram.
Syntax: Axes.hist(self, x, bins=None, range=None, density=None, weights=None, cumulative=False, bottom=None, histtype=’bar’, align=’mid’, orientation=’vertical’, rwidth=None, log=False, color=None, label=None, stacked=False, normed=None, *, data=None, **kwargs)
Parameters: This method accept the following parameters that are described below:
x : This parameter are the sequence of data.
bins : This parameter is an optional parameter and it contains the integer or sequence or string.
range : This parameter is an optional parameter and it the lower and upper range of the bins.
density : This parameter is an optional parameter and it contains the boolean values.
weights : This parameter is an optional parameter and it is an array of weights, of the same shape as x.
bottom : This parameter is the location of the bottom baseline of each bin.
histtype : This parameter is an optional parameter and it is used to draw type of histogram. {‘bar’, ‘barstacked’, ‘step’, ‘stepfilled’}
align : This parameter is an optional parameter and it controls how the histogram is plotted. {‘left’, ‘mid’, ‘right’}
rwidth : This parameter is an optional parameter and it is a relative width of the bars as a fraction of the bin width
log : This parameter is an optional parameter and it is used to set histogram axis to a log scale
color : This parameter is an optional parameter and it is a color spec or sequence of color specs, one per dataset.
label : This parameter is an optional parameter and it is a string, or sequence of strings to match multiple datasets.
normed : This parameter is an optional parameter and it contains the boolean values.It uses the density keyword argument instead.
Returns: This returns the following:
n :This returns the values of the histogram bins.
bins :This returns the edges of the bins.
patches :This returns the list of individual patches used to create the histogram.
Below examples illustrate the matplotlib.axes.Axes.hexbin() function in matplotlib.axes:
Example-1:
# Implementation of matplotlib functionimport matplotlibimport numpy as npimport matplotlib.pyplot as plt  np.random.seed(10**7)mu = 121  sigma = 21x = mu + sigma * np.random.randn(1000)  num_bins = 100fig, ax = plt.subplots()  n, bins, patches = ax.hist(x, num_bins,                           density = 1,                            color ='green',                            alpha = 0.7)  y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))ax.plot(bins, y, '--', color ='black')ax.set_xlabel('X-Axis')ax.set_ylabel('Y-Axis')  ax.set_title('matplotlib.axes.Axes.hist() Example')plt.show()
Output:
Example-2:
# Implementation of matplotlib functionimport matplotlibimport numpy as npimport matplotlib.pyplot as plt  np.random.seed(10**7)n_bins = 20x = np.random.randn(10000, 3)  fig, [(ax0, ax1), (ax2, ax3)] = plt.subplots(nrows = 2,                                             ncols = 2)    colors = ['green', 'blue', 'lime']  ax0.hist(x, n_bins, density = True,          histtype ='bar',         color = colors,          label = colors)  ax0.legend(prop ={'size': 10})  ax1.hist(x, n_bins, density = True,         histtype ='barstacked',         stacked = True,          color = colors)  ax2.hist(x, n_bins, histtype ='step',         stacked = True,         fill = False,          color = colors)  x_multi = [np.random.randn(n) for n in [100000,                                        80000,                                        1000]]  ax3.hist(x_multi, n_bins,          histtype ='stepfilled',         color = colors)  plt.show()
Output:
Python-matplotlib
Python
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