Python matplotlib模块 Python matplotlib模块及柱状图用法解析

import matplotlib.pyplot as plt
import numpy as np
 
def test4():
  names = ['电影1', '电影2', '电影3']
  real_num1 = [7548, 4013, 1673]
  real_num2 = [5453, 1840, 1080]
  real_num3 = [4348, 2345, 1890]
  x = np.arange(len(names))
  # 绘制柱形图
  width = 0.3
  plt.bar(x, real_num1, alpha=0.5, width=width, label=names[0])
  plt.bar([i+width for i in x], real_num2, alpha=0.5, width=width, label=names[1])
  plt.bar([i+2*width for i in x], real_num3, alpha=0.5, width=width, label=names[2])
  # 正常显示中文
  plt.rcParams["font.sans-serif"] = ["SimHei"]
  # 设置x坐标轴的值
  x_label = ["第{}天".format(i+1) for i in x]
  # 让x坐标轴显示在中间
  plt.xticks([i+width for i in x], x_label)
  # 添加ylabel
  plt.ylabel("票房数")
  # 添加图例
  plt.legend()
  # 添加标题
  plt.title("3天3部电影票房数")
  plt.show()
 
test4()

from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as np
 
def test5():
  # ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap='rainbow') #绘面
  # 绘制3D曲面图
  fig = plt.figure()
  ax = Axes3D(fig)
  # -4 到4 [-4, 4)，步长为0.25
  X = np.arange(-4, 4, 0.25)
  Y = np.arange(-4, 4, 0.25)
  # meshgrid方法，你只需要构造一个表示x轴上的坐标的向量和一个表示y轴上的坐标的向量;然后作为参数给到meshgrid(),该函数就会返回相应维度的两个矩阵;
  X, Y = np.meshgrid(X, Y)
  R = np.sqrt(X**2 + Y ** 2)
  Z = np.sin(R)
  ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap="rainbow")
  plt.show()

import matplotlib.pyplot as plt
import numpy as np
def test6():
  # 绘制三维散点图
  # ax.scatter(x[1000:4000],y[1000:4000],z[1000:4000],c='r') #绘点
  data = np.random.randint(0, 255, size=[40, 40, 40])
  x, y, z = data[0], data[1], data[2]
  # 创建一个三维的绘图工程
  ax = plt.subplot(111, projection="3d")
  # 将数据点分成三部分画，在颜色上有区分度
  ax.scatter(x[:10], y[:10], z[:10], c='y') # 绘制数据点
  ax.scatter(x[10:20], y[10:20], z[10:20], c='r')
  ax.scatter(x[30:40], y[30:40], z[30:40], c='g')
  # 坐标轴
  ax.set_zlabel("Z")
  ax.set_ylabel("Y")
  ax.set_xlabel("X")
  plt.show()