Matplotlib.axes.Axes.hist() in Python

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.hist() Function

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:

filter_none

edit
close

play_arrow

link
brightness_4
code

# Implementation of matplotlib function
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
  
np.random.seed(10**7)
mu = 121  
sigma = 21
x = mu + sigma * np.random.randn(1000)
  
num_bins = 100
fig, 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()

chevron_right


Output:

Example-2:

filter_none

edit
close

play_arrow

link
brightness_4
code

# Implementation of matplotlib function
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
  
np.random.seed(10**7)
n_bins = 20
x = 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()

chevron_right


Output:




My Personal Notes arrow_drop_up

Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.


Article Tags :

Be the First to upvote.


Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.