Matplotlib 绘图笔记

文章目录

简介
应用
代码实操
- 折线图绘制与显示
- 绘制数学函数图像
- 散点图绘制
- 绘制柱状图
- 绘制直方图
- 饼图

简介

Matplotlib 是 Python 的绘图库，它能让使用者很轻松地将数据图形化，并且提供多样化的输出格式。

Matplotlib 可以用来绘制各种静态，动态，交互式的图表。

Matplotlib 是一个非常强大的 Python 画图工具，我们可以使用该工具将很多数据通过图表的形式更直观的呈现出来。

Matplotlib 可以绘制线图、散点图、等高线图、条形图、柱状图、3D 图形、甚至是图形动画等等。

Matplotlib是Python编程语言及其数值数学扩展NumPy的绘图库。它提供面向对象的API，用于使用通用GUI 工具包（如Tkinter、wxPython、Qt或GTK ）将绘图嵌入到应用程序中。还有一个基于状态机（如OpenGL ）的过程“pylab”接口，其设计与MATLAB非常相似，但不鼓励使用它。[3]科学使用 Matplotlib。

Matplotlib 最初由John D. Hunter编写。从那时起，它就有了一个活跃的开发社区[4]，并在BSD 风格的许可下分发。Michael Droettboom 在 John Hunter 于 2012 年 8 月去世前不久被提名为 matplotlib 的首席开发人员[5]，Thomas Caswell 进一步加入。[6] [7] Matplotlib 是NumFOCUS财政赞助的项目。[8]

Matplotlib 2.0.x 支持 Python 版本 2.7 到 3.10。Python 3 支持从 Matplotlib 1.2 开始。Matplotlib 1.4 是最后一个支持 Python 2.6 的版本。[9] Matplotlib 通过签署 Python 3 声明承诺在 2020 年之后不再支持 Python 2。[10]

应用

Matplotlib 通常与 NumPy 和 SciPy（Scientific Python）一起使用，这种组合广泛用于替代 MatLab，是一个强大的科学计算环境，有助于我们通过 Python 学习数据科学或者机器学习。

SciPy 是一个开源的 Python 算法库和数学工具包。

SciPy 包含的模块有最优化、线性代数、积分、插值、特殊函数、快速傅里叶变换、信号处理和图像处理、常微分方程求解和其他科学与工程中常用的计算。

代码实操

选择monokai绘图主题

from jupyterthemes import jtplot
jtplot.style(theme='monokai')import matplotlib.pyplot as plt
# 个别环境需要以下代码
%matplotlib inline

plt.figure()
plt.plot([1,0,9],[4,5,6])
plt.show()

折线图绘制与显示

展现一周天气
1.创建画布
figsize:指定图的长宽
dpi:图像清晰度
返回fig对象


plt.figure(figsize=(20,8))
# plt.figure(figsize=(),dpi=)

2.绘制图像

plt.plot([1,2,3,4,5,6,7],[17,17,18,15,11,11,13],label="hh")
# plt.plot(x,y,color=,linestyle=",label=")
# figure, axes = plt.subplots(nrows=1, ncols=2, figsize=(20,8), dpi=80)显示图例
```python
plt.legend(loc="lower left")

添加网格显示

plt.grid(True,linestyle='-',alpha=0.5)

3.保存图像必须放在show的前边，因为show会释放图像资源

plt.savefig("test.png")

4.显示图像

plt.show()

绘制数学函数图像

import numpy as np

1.准备x,y数据

x = np.linspace(-1,1,1000)
y = 2 * x * x

2.创建画布

plt.figure(figsize=(20,8), dpi=80)

3.绘制图像

plt.plot(x,y)

4.显示图像

plt.show()

散点图绘制

1.准备数据

x, y = [1,2,3,4,5,6,7], [17,17,18,15,11,11,13]

2.创建画布

plt.figure(figsize=(20, 8))

3.绘制图像

plt.scatter(x,y)

4.显示图像

plt.show()

绘制柱状图

1.准备数据

x, y = [1,2,3,4,5,6,7], [17,17,2,15,11,11,13]

2.创建画布

plt.figure(figsize=(20, 8))

3.绘制图像

plt.bar(x,y,width=0.5,color=['r','b','y','g'])

4.显示图像

plt.show()

绘制直方图

x = [1,2,3,4,5,6,17,17,18,15,11,45,12,54,23,45,6,12,87,51,11,13]plt.figure(figsize=(20,8), dpi=80)distance = 2
group_num = int((max(x) - min(x)) / distance)plt.hist(x, bins=group_num)plt.show()

饼图

1.准备数据


x, y = [1,2,3,4,5,6,7], ['17','17','2','15','11','11','13']

2.创建画布

plt.figure(figsize=(20, 8))

3.绘制图像

plt.pie(x,labels=y,autopct='%1.2f%%',colors=['r','b','y','g'])

x,y轴刻度等长

plt.axis('equal')
plt.legend(loc="lower left")

4.显示图像

plt.show()

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