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📜  Matplotlib-直方图

📅  最后修改于: 2020-11-08 07:27:46             🧑  作者: Mango

直方图是数字数据分布的准确表示。它是对连续变量的概率分布的估计。它是一种条形图。

要构建直方图，请按照以下步骤操作：

  • Bin值的范围。
  • 将整个值范围划分为一系列间隔。
  • 计算每个间隔内有多少个值。

通常将bin指定为变量的连续，不重叠的间隔。

matplotlib.pyplot.hist()函数绘制直方图。它计算并绘制x的直方图。

参量

下表列出了直方图的参数-

x array or sequence of arrays
bins integer or sequence or ‘auto’, optional
optional parameters
range The lower and upper range of the bins.
density If True, the first element of the return tuple will be the counts normalized to form a probability density
cumulative If True, then a histogram is computed where each bin gives the counts in that bin plus all bins for smaller values.
histtype The type of histogram to draw. Default is ‘bar’
  • ‘bar’ is a traditional bar-type histogram. If multiple data are given the bars are arranged side by side.
  • ‘barstacked’ is a bar-type histogram where multiple data are stacked on top of each other.
  • ‘step’ generates a lineplot that is by default unfilled.
  • ‘stepfilled’ generates a lineplot that is by default filled.

以下示例绘制了班级学生获得的分数直方图。定义了四个容器0-25、26-50、51-75和76-100。直方图显示落入该范围的学生人数。

from matplotlib import pyplot as plt
import numpy as np
fig,ax = plt.subplots(1,1)
a = np.array([22,87,5,43,56,73,55,54,11,20,51,5,79,31,27])
ax.hist(a, bins = [0,25,50,75,100])
ax.set_title("histogram of result")
ax.set_xticks([0,25,50,75,100])
ax.set_xlabel('marks')
ax.set_ylabel('no. of students')
plt.show()

该图如下所示-

直方图