text: import pandas as pd
  import matplotlib.pyplot as plt
  from scipy.stats import linregress
  
  def draw_plot():
      # Read data from file
      df = pd.read_csv("epa-sea-level.csv")
  
      # Create scatter plot
      plt.figure(figsize = (16, 5))
      plt.scatter(x = df['Year'], y = df["CSIRO Adjusted Sea Level"])
      
      # Create first line of best fit
      first_x = []
      first_y = []
      first_slope, first_intercept, _, _, _ = linregress(df['Year'], df["CSIRO Adjusted Sea Level"])
      for i in range(1880, 2051):
        first_x.append(i)
        first_y.append(first_slope * i + first_intercept)
      plt.plot(first_x, first_y, 'g')
      
      # Create second line of best fit
      df = df[df.Year >= 2000]
      second_x = []
      second_y = []
      second_slope, second_intercept, _, _, _ = linregress(df['Year'], df["CSIRO Adjusted Sea Level"])
      for i in range(2000, 2051):
        second_x.append(i)
        second_y.append(second_slope * i + second_intercept)
      plt.plot(second_x, second_y, 'r')
      
      # Add labels and title
      plt.title("Rise in Sea Level")
      plt.xlabel("Year")
      plt.ylabel("Sea Level (inches)")
      
      # Save plot and return data for testing (DO NOT MODIFY)
      plt.savefig('sea_level_plot.png')
      return plt.gca()
  