conda install matplotlib

pip install matplotlib

import matplotlib.pyplot as plt

# 時(shí)間序列數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y = [10, 15, 13, 18, 16]

# 創(chuàng)建折線圖
plt.plot(x, y)

# 添加標(biāo)題和標(biāo)簽
plt.title('Simple Line Plot')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt

# 不同類別的數(shù)據(jù)
categories = ['A', 'B', 'C', 'D']
values = [20, 35, 30, 25]

# 創(chuàng)建柱狀圖
plt.bar(categories, values)

# 添加標(biāo)題和標(biāo)簽
plt.title('Bar Chart Example')
plt.xlabel('Categories')
plt.ylabel('Values')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt

# 兩個變量的數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y = [10, 15, 13, 18, 16]

# 創(chuàng)建散點(diǎn)圖
plt.scatter(x, y)

# 添加標(biāo)題和標(biāo)簽
plt.title('Scatter Plot Example')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt

# 數(shù)據(jù)和對應(yīng)的標(biāo)簽
sizes = [30, 20, 25, 25]
labels = ['A', 'B', 'C', 'D']

# 創(chuàng)建餅圖
plt.pie(sizes, labels=labels, autopct='%1.1f%%')

# 添加標(biāo)題
plt.title('Pie Chart Example')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
np.random.seed(10)
data = np.random.normal(loc=0, scale=1, size=100)

# 創(chuàng)建箱線圖
plt.boxplot(data)

# 添加標(biāo)題
plt.title('Box Plot Example')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)矩陣
data = np.random.rand(10, 10)

# 創(chuàng)建熱圖
plt.imshow(data, cmap='hot', interpolation='nearest')

# 添加顏色條
plt.colorbar()

# 添加標(biāo)題
plt.title('Heatmap Example')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt

# 時(shí)間序列數(shù)據(jù)
x = [1, 2, 3, 4, 5]
y1 = [10, 15, 13, 18, 16]
y2 = [8, 12, 10, 14, 11]

# 創(chuàng)建面積圖
plt.fill_between(x, y1, color='skyblue', alpha=0.4, label='Y1')
plt.fill_between(x, y2, color='salmon', alpha=0.4, label='Y2')

# 添加標(biāo)題和標(biāo)簽
plt.title('Area Plot Example')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# 添加圖例
plt.legend()

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
np.random.seed(0)
x = np.random.standard_normal(100)
y = np.random.standard_normal(100)
z = np.random.standard_normal(100)

# 創(chuàng)建 3D 散點(diǎn)圖
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(x, y, z)

# 添加標(biāo)題
plt.title('3D Scatter Plot Example')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
x = np.linspace(0, 10, 100)
y = np.sin(x)

# 創(chuàng)建圖表并設(shè)置自定義樣式
with plt.style.context('seaborn-darkgrid'):
    plt.plot(x, y, label='sin(x)')
    plt.title('Custom Style Example')
    plt.xlabel('X-axis')
    plt.ylabel('Y-axis')
    plt.legend()

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
x = np.linspace(0, 10, 100)
y1 = np.sin(x)
y2 = np.cos(x)

# 創(chuàng)建子圖
fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.plot(x, y1)
ax1.set_title('sin(x)')
ax2.plot(x, y2)
ax2.set_title('cos(x)')

# 調(diào)整子圖布局
plt.tight_layout()

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
x = np.linspace(0, 10, 10)
y = np.sin(x)
error = 0.1 * np.abs(y)  # 模擬誤差范圍

# 創(chuàng)建帶誤差棒的折線圖
plt.errorbar(x, y, yerr=error, fmt='-o', ecolor='red', capsize=5)

# 添加標(biāo)題和標(biāo)簽
plt.title('Error Bar Plot Example')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np
import time

# 創(chuàng)建空圖表
plt.ion()

# 初始化數(shù)據(jù)
x = np.linspace(0, 10, 100)
y = np.sin(x)

# 動態(tài)更新折線圖
for i in range(10):
    y += 0.1 * np.random.normal(size=len(x))  # 模擬數(shù)據(jù)更新
    plt.plot(x, y, '-o')
    plt.title('Dynamic Line Plot Example')
    plt.xlabel('X-axis')
    plt.ylabel('Y-axis')
    plt.draw()
    plt.pause(0.5)
    plt.clf()  # 清空圖表以便更新下一幀數(shù)據(jù)

# 關(guān)閉交互模式
plt.ioff()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
x = np.linspace(0, 10, 100)
y = np.sin(x)

# 創(chuàng)建折線圖
plt.plot(x, y)
plt.title('Save Figure Example')
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# 保存圖表為 PNG 文件
plt.savefig('figure.png')

# 保存圖表為 PDF 文件
plt.savefig('figure.pdf')

# 顯示圖表
plt.show()

import matplotlib.pyplot as plt
import numpy as np

# 生成隨機(jī)數(shù)據(jù)
data = np.random.randn(1000)

# 創(chuàng)建直方圖
plt.hist(data, bins=30, edgecolor='black')

# 添加標(biāo)題和標(biāo)簽
plt.title('Histogram Example')
plt.xlabel('Value')
plt.ylabel('Frequency')

# 顯示圖表
plt.show()