如何在 Matplotlib 中一起绘制两个直方图？
原文:https://www . geeksforgeeks . org/如何在 matplotlib 中绘制两个直方图/
先决条件:
直方图是将分组数据点组织到指定范围内的图形表示。创建直方图提供了数据分布的可视化表示。通过使用直方图，我们可以将大量数据及其频率表示为一个连续的图。
使用的功能
为了在 Matplotlib 中创建直方图，我们使用了属于 pyplot 模块的 hist()函数。为了一起绘制两个直方图，我们必须通过给定一些设置，对两个数据集分别使用 hist()函数。
语法:
matplotlib.pyplot.hist(x，bins，edgecolor，label)
参数:
| **参数** | **描述** | | x | 用于绘制直方图的数组或数据集 | | 垃圾箱 | 用于区间的整数值或序列 | | edgecolor 或 ec | 设置直方图条的边缘颜色 | | 颜色 | 设置直方图条的条颜色 | | 标签 | 用于表示直方图的标签，它是字符串类型。 | | 希腊字母的第一个字母 | 用于设置透明度。 | | 标签 | 用于表示直方图的名称或标签。 |方法
- 导入模块
- 为两个数据集创建或加载数据
- 分别绘制两个数据帧的直方图
- 把它们连在一起
例 1:
计算机编程语言
# importing libraries
import matplotlib.pyplot as plt
import numpy as np
# generating two series of random
# values using numpy random module
# of shape (500,1)
series1 = np.random.randn(500, 1)
series2 = np.random.randn(400, 1)
# plotting first histogram
plt.hist(series1)
# plotting second histogram
plt.hist(series2)
# Showing the plot using plt.show()
plt.show()
输出:
例 2:
计算机编程语言
# importing libraries
import matplotlib.pyplot as plt
import numpy as np
from numpy.lib.histograms import histogram
# generating two series of random values
# using numpy random module of shape (500,1)
series1 = np.random.randn(500, 1)
series2 = np.random.randn(400, 1)
# plotting first histogram
plt.hist(series1, label='series1', alpha=.8, edgecolor='red')
# plotting second histogram
plt.hist(series2, label='series2', alpha=0.7, edgecolor='yellow')
plt.legend()
# Showing the plot using plt.show()
plt.show()
输出:
示例 3: 代表两个年龄组的直方图
计算机编程语言
# importing libraries
import matplotlib.pyplot as plt
# giving two age groups data
age_g1 = [1, 3, 5, 10, 15, 17, 18, 16, 19, 21,
23, 28, 30, 31, 33, 38, 32, 40, 45,
43, 49, 55, 53, 63, 66, 85, 80, 57,
75, 93, 95]
age_g2 = [6, 4, 15, 17, 19, 21, 28, 23, 31, 36,
39, 32, 50, 56, 59, 74, 79, 34, 98, 97,
95, 67, 69, 92, 45, 55, 77, 76, 85]
# plotting first histogram
plt.hist(age_g1, label='Age group1', alpha=.7, edgecolor='red')
# plotting second histogram
plt.hist(age_g2, label='Age group2', alpha=0.7, edgecolor='yellow')
plt.legend()
# Showing the plot using plt.show()
plt.show()
输出:
例 4:
计算机编程语言
# importing libraries
import matplotlib.pyplot as plt
# giving two age groups data
age_g1 = [1, 3, 5, 10, 15, 17, 18, 16, 19,
21, 23, 28, 30, 31, 33, 38, 32,
40, 45, 43, 49, 55, 53, 63, 66,
85, 80, 57, 75, 93, 95]
age_g2 = [6, 4, 15, 17, 19, 21, 28, 23, 31,
36, 39, 32, 50, 56, 59, 74, 79, 34,
98, 97, 95, 67, 69, 92, 45, 55, 77,
76, 85]
# plotting first histogram
plt.hist(age_g1, label='Age group1', bins=14, alpha=.7, edgecolor='red')
# plotting second histogram
plt.hist(age_g2, label="Age group2", bins=14, alpha=.7, edgecolor='yellow')
plt.legend()
# Showing the plot using plt.show()
plt.show()
输出:
示例 5 :改变默认的条形颜色
计算机编程语言
# importing libraries
import matplotlib.pyplot as plt
# giving two age groups data
age_g1 = [1, 3, 5, 10, 15, 17, 18, 16, 19, 21,
23, 28, 30, 31, 33, 38, 32, 40, 45,
43, 49, 55, 53, 63, 66, 85, 80, 57,
75, 93, 95]
age_g2 = [6, 4, 15, 17, 19, 21, 28, 23, 31, 36,
39, 32, 50, 56, 59, 74, 79, 34, 98, 97,
95, 67, 69, 92, 45, 55, 77, 76, 85]
# plotting first histogram
plt.hist(age_g1, label='Age group1', alpha=.7, color='red')
# plotting second histogram
plt.hist(age_g2, label="Age group2", alpha=.5,
edgecolor='black', color='yellow')
plt.legend()
# Showing the plot using plt.show()
plt.show()
输出:
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