Histogram of pyplot module of Matplotlib (hist(): basic parameter, return value)

Histogram

Concept : Histogram is used to measure the probability distribution of continuous variables .

Parameters,

Use matplotlib Draw histogram :

Histogram has only one parameter x！！！ Unlike a bar chart that needs to be passed in x,y

plt.hist(
    x,
    bins=None,
    range=None,
    density=False,
    weights=None,
    cumulative=False,
    bottom=None,
    histtype='bar',
    align='mid',
    orientation='vertical',
    rwidth=None,
    log=False,
    color=None,
    label=None,
    stacked=False,
    *,
    data=None,
    **kwargs,
)

hist() Parameters of

• x: input data
• bins： It could be a bins The integer value of the quantity , It can also mean bins A sequence of . The default value is 10

bins（ Divide the value into equal parts ）, That is to say, we need to divide the continuous value into different equal parts first , Then calculate the amount of data in each copy .

• range
  Set up X Start and end scales of axis scale

• density： If the value is True, The value of histogram will be normalized , Formation probability density , The default value is False

• color： Specifies the color of the histogram . Can be a single color value or a sequence of colors . If more than one data set is specified , The color sequence will be set to the same order . If not specified , A default line color will be used

• orientation： By setting orientation by horizontal Create a horizontal histogram . The default value is vertical

• align：{'left', 'mid', 'right'}, default: 'mid'

  • left： The bar chart is located on the left edge .
  • 'mid'： The bar graph is in the center .
  • 'right'： The bar chart is located on the right edge .

• label： Add legend

• rwidth： The relative width of the bar

Parameter examples and explanations

import numpy as np
x = np.random.randint(1,10,size = 10)
#  Show me  rwidth  The role of 
print(x)
plt.hist(x, bins=5, rwidth=0.5, range = (0, 10), color = "red", label=' Statistics ')  #  Divide the histogram into 5 Share ,  Show the distribution frequency 
plt.legend()
plt.show()

label: After declaring the legend , Use legend(), To display
rwidth： Set the proportion of graphics x The proportion of the shaft
range： Set up X The interval of the axis scale

Code run results

bins Analyze by setting the list as interval and return value

print(x)
n, bins, patches = plt.hist(x, bins=[1,3,5,8,10], rwidth=0.5)
plt.show()

• What we specify is the edge of the interval , Each interval is [1,3) [3,5) [5,8) [8,10],
• rwidth： Will follow the interval 0.5 To display , such as x Axis 1 To 3 Half of ,5 To 8 Half of ,
• Except for the last interval , All intervals are left closed and right open
• And the length of each interval need not be equal
• Data outside our specified interval will be directly ignored

notes ： If bins In list form , be range It has no effect

print(' Number distribution ：', n)
print(' Interval division :', bins)
print(patches)

n： Means falling into each bins Number of samples in
bins: Partition interval of table interval
patches： Patch objects, I don't understand

Code run results

density

print(x)
n, bins, patches = plt.hist(x, bins=[1,3,5,8,10], rwidth=0.5, density=True)
plt.show()
print(' Number distribution ：', n)
print(' Interval division :', bins)
print(patches)

• density Set to True when , The vertical axis shows the distribution frequency
• n This is the value of the distribution frequency
  

Reference article

Matplotlib Official Manual address
python Draw histogram matplotlib.pyplot.hist( ) Methods common parameters are explained in detail

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