text: import pandas as pd
  import matplotlib.pyplot as plt
  import numpy as np
  
  
  def zseita():
      # 读取数据文件
      df = pd.read_excel("/Users/dingding/Desktop/Angle/5.6/containseita5.xlsx")
      # 取出身高和体重两列数据
      z = df['z']
      seita = df['seita']
      plt.figure(figsize=(10, 5))
      plt.scatter(z, seita,s=5,alpha=1,marker='o',c='r')
      # x，y取值范围设置
      # 可以过滤掉一部分脏数据
  
      plt.xlim(0, 5.5)
      plt.ylim(0, 1.5)
      plt.axis()
      # 设置title和x，y轴的label
      plt.title("Z-seita")
      plt.xlabel("z")
      plt.ylabel("seita[degree]")
      # 保存图片到指定路径
      # plt.savefig("/Users/dingding/Desktop/zseita.jpg")
      # 展示图片 *必加
      plt.show()
  
  
  def zeiso():
      df = pd.read_excel("/Users/dingding/Desktop/Angle/5.6/containseita5.xlsx")
      z = df['z']
      eiso = df['eisocalculate']
      plt.figure(figsize=(10, 5))
      plt.scatter(z, np.log10(eiso), s=5, alpha=1, marker='o', c='r')
      plt.xlim(0, 5.5)
      # plt.ylim(10**48, 10**55)
      plt.axis()
      plt.title("Z-Eisocalculate")
      plt.xlabel("z")
      plt.ylabel("Eiso")
      plt.savefig("/Users/dingding/Desktop/zEiso.jpg")
      plt.show()
  
  def zegamma():
      df = pd.read_excel("/Users/dingding/Desktop/Angle/5.6/containseita5.xlsx")
      z = df['z']
      egamma = df['egammacalculate']
      plt.figure(figsize=(10, 5))
      plt.scatter(z, np.log10(egamma), s=5, alpha=1, marker='o', c='r')
      plt.xlim(0, 5.5)
      # plt.ylim(0, 1.5)
      plt.axis()
      plt.title("Z-Egammacalculate")
      plt.xlabel("z")
      plt.ylabel("Egamma")
      plt.savefig("/Users/dingding/Desktop/zEgamma.jpg")
      plt.show()
  
  # zseita()
  zeiso()
  zegamma()
  