"""
=========================================================
Demo of the histogram (hist) function with a few features
=========================================================

In addition to the basic histogram, this demo shows a few optional
features:

    * Setting the number of data bins
    * The ``normed`` flag, which normalizes bin heights so that the
      integral of the histogram is 1. The resulting histogram is an
      approximation of the probability density function.
    * Setting the face color of the bars
    * Setting the opacity (alpha value).

Selecting different bin counts and sizes can significantly affect the
shape of a histogram. The Astropy docs have a great section on how to
select these parameters:
http://docs.astropy.org/en/stable/visualization/histogram.html
"""

import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

np.random.seed(0)

# example data
mu = 100  # mean of distribution
sigma = 15  # standard deviation of distribution
x = mu + sigma * np.random.randn(437)

num_bins = 50

fig, ax = plt.subplots()

# the histogram of the data
n, bins, patches = ax.hist(x, num_bins, normed=1)

# add a 'best fit' line
y = mlab.normpdf(bins, mu, sigma)
ax.plot(bins, y, '--')
ax.set_xlabel('Smarts')
ax.set_ylabel('Probability density')
ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')

# Tweak spacing to prevent clipping of ylabel
fig.tight_layout()
plt.show() 

　

Traceback (most recent call last):
  File "M:\______\histogram_demo_features.py", line 38, in 
    n, bins, patches = ax.hist(x, num_bins, normed=1)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\______\AppData\Local\Programs\Python\Python311\Lib
    \site-packages\matplotlib\__init__.py", line 1459, in inner
    return func(ax, *map(sanitize_sequence, args), **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\______\AppData\Local\Programs\Python\Python311\Lib
    \site-packages\matplotlib\axes\_axes.py", line 6943, in hist
    p._internal_update(kwargs)
  File "C:\Users\______\AppData\Local\Programs\Python\Python311\Lib
    \site-packages\matplotlib\artist.py", line 1223, in _internal_update
    return self._update_props(
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Users\______\AppData\Local\Programs\Python\Python311\Lib
    \site-packages\matplotlib\artist.py", line 1197, in _update_props
    raise AttributeError(
AttributeError: Rectangle.set() got an unexpected keyword argument 'normed' 

Traceback (most recent call last):
  File "E:\______\histogram_demo_features.py", line 38, in 
    n, bins, patches = ax.hist(x, num_bins, normed=1)
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Program Files\Python312\Lib\site-packages\matplotlib\__init__.py", 
    line 1478, in inner
    return func(ax, *map(sanitize_sequence, args), **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Program Files\Python312\Lib\site-packages\matplotlib\axes\_axes.py", 
    line 7012, in hist
    p._internal_update(kwargs)
  File "C:\Program Files\Python312\Lib\site-packages\matplotlib\artist.py", 
    line 1219, in _internal_update
    return self._update_props(
           ^^^^^^^^^^^^^^^^^^^
  File "C:\Program Files\Python312\Lib\site-packages\matplotlib\artist.py", 
    line 1193, in _update_props
    raise AttributeError(
AttributeError: Rectangle.set() got an unexpected keyword argument 'normed' 

"""
==============================================
Some features of the histogram (hist) function
==============================================

In addition to the basic histogram, this demo shows a few optional features:

* Setting the number of data bins.
* The *density* parameter, which normalizes bin heights so that the integral of
  the histogram is 1. The resulting histogram is an approximation of the
  probability density function.

Selecting different bin counts and sizes can significantly affect the shape
of a histogram. The Astropy docs have a great section_ on how to select these
parameters.

.. _section: http://docs.astropy.org/en/stable/visualization/histogram.html
"""

import matplotlib.pyplot as plt
import numpy as np

rng = np.random.default_rng(19680801)

# example data
mu = 106  # mean of distribution
sigma = 17  # standard deviation of distribution
x = rng.normal(loc=mu, scale=sigma, size=420)

num_bins = 42

fig, ax = plt.subplots()

# the histogram of the data
n, bins, patches = ax.hist(x, num_bins, density=True)

# add a 'best fit' line
y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *
     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))
ax.plot(bins, y, '--')
ax.set_xlabel('Value')
ax.set_ylabel('Probability density')
ax.set_title('Histogram of normal distribution sample: '
             fr'$\mu={mu:.0f}$, $\sigma={sigma:.0f}$')

# Tweak spacing to prevent clipping of ylabel
fig.tight_layout()
plt.show()

# %%
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.axes.Axes.hist` / `matplotlib.pyplot.hist`
#    - `matplotlib.axes.Axes.set_title`
#    - `matplotlib.axes.Axes.set_xlabel`
#    - `matplotlib.axes.Axes.set_ylabel` 

　Python 3.11.6 (matplotlib 3.7.1) 及び Python 3.12.0 (matplotlib 3.8.1) 共に、正常実行です。

　

• 2023/12/10 Ver=1.04 Python 3.12.0 (matplotlib 3.8.1)で確認
• 2023/12/10 Ver=1.04 Python 3.11.6 (matplotlib 3.7.1)で確認
• 2023/04/05 Ver=1.03 Python 3.11.2 で確認
• 2020/11/02 Ver=1.01 Python 3.7.8 で確認
• 2018/12/06 Ver=1.01 初版リリース

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