Python可视化与交互matplotlib库的详细介绍

import matplotlib.pyplot as plt
import numpy as np

# 画图基本逻辑
## 准备数据
x = np.linspace(0, 10, 100)
y = np.sin(x)

## 创建画布和容器
fig, ax = plt.subplots()

## 绘制图形
ax.plot(x, y)

# 自定义图形
ax.set_title('Sine Wave')   # 设置标题
ax.set_xlabel('x')          # 设置横坐标标签
ax.set_ylabel('sin(x)')     # 设置纵坐标标签
ax.grid(True)               # 显示网格

# 显示图形
plt.show()

x = np.random.rand(100)
y = np.random.rand(100)

fig, ax = plt.subplots()

ax.scatter(x, y)

ax.set_title("Scatter")
ax.set_xlabel("X")
ax.set_ylabel("Y")
ax.grid(True)

# 柱状图
categories = ['A', 'B', 'C', 'D', 'E', 'F']
values = [79, 68, 89, 94, 54, 77]

fig, ax = plt.subplots()

ax.bar(categories, values)

ax.set_title("Bar")
ax.set_xlabel("Student")
ax.set_ylabel("Scores")

plt.show()

# 直方图
data = np.random.randn(1000)

fig, ax = plt.subplots()

ax.hist(data, bins = 100, color = "green", alpha = 0.75)

ax.set_title("Histogram")
ax.set_xlabel("Value")
ax.set_ylabel("Frequency")
ax.grid(True)

plt.show()

# 多子图绘制
x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)

fig, axs = plt.subplots(1, 2, figsize=(10, 8))

axs[0].plot(x, y1)
axs[0].set_title('sin(x)')
axs[0].set_xlabel('x')
axs[0].set_ylabel('sin(x)')
axs[0].grid(True)

axs[1].plot(x, y2)
axs[1].set_title('cos(x)')
axs[1].set_xlabel('x')
axs[1].set_ylabel('cos(x)')
axs[1].grid(True)

fig.suptitle('sin(x) VS. cos(x)', fontsize = 18)

plt.show()

import matplotlib.pyplot as plt
from netCDF4 import Dataset

## 准备数据
file_path = "C:/Users/hang/Downloads/test.grd"
nc = Dataset(file_path, 'r')
lon = nc.variables['lon'][:]
lat = nc.variables['lat'][:]
z = nc.variables['z'][:]
nc.close()

## 创建画布和容器
fig, ax = plt.subplots(figsize = (10, 8))

## 图形绘制
## pcolormesh是一个用于绘制二维网格数据的函数，能够将数值映射为颜色
mesh = ax.pcolormesh(lon, lat, z, cmap = 'jet', shading = 'auto')

## 图形编辑
cbar = fig.colorbar(mesh, ax = ax)
cbar.set_label('Height', fontsize = 14)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.grid(True)

plt.show()