text: import numpy as np
  import matplotlib.pyplot as plt
  import pandas as pd
  from scipy.interpolate import spline
  import time
  
  
  tweets=pd.read_csv("final_incomplete_tweets.csv",sep =',')
  
  tweets_org=tweets[['inverted_loss','entry_vs_tweet_seen_ratio']].groupby(["entry_vs_tweet_seen_ratio"]).mean()
  
  # x = tweets_org['inverted_loss']
  # y = tweets_org.index.values
  tweets_org=tweets_org.reset_index()
  
  x= tweets_org['entry_vs_tweet_seen_ratio'].tolist()
  y = tweets_org['inverted_loss'].tolist()
  # print(y)
  
  # Create a canvas to place the subgraphs
  canvas = plt.figure()
  rect = canvas.patch
  rect.set_facecolor('white')
  
  
  x_sm = np.array(x)
  y_sm = np.array(y)
  
  x_smooth = np.linspace(x_sm.min(), x_sm.max(), 100)
  y_smooth = spline(x, y, x_smooth)
  
  print(y_sm,y_smooth,y_sm.min(),y_sm.max())
  # Define the matrix of 1x1 to place subplots
  # Placing the plot1 on 1x1 matrix, at pos 1
  sp1 = canvas.add_subplot(1,1,1, axisbg='w')
  #sp1.plot(x, y, 'red', linewidth=2)
  sp1.plot(x_smooth, y_smooth, 'red', linewidth=1)
  
  # Colorcode the tick tabs 
  sp1.tick_params(axis='x', colors='red')
  sp1.tick_params(axis='y', colors='red')
  
  # Colorcode the spine of the graph
  sp1.spines['bottom'].set_color('r')
  sp1.spines['top'].set_color('r')
  sp1.spines['left'].set_color('r')
  sp1.spines['right'].set_color('r')
  
  # Put the title and labels
  sp1.set_title('matplotlib example 1', color='red')
  sp1.set_xlabel('matplot x label', color='red')
  sp1.set_ylabel('matplot y label', color='red')
  
  # Show the plot/image
  plt.tight_layout()
  plt.grid(alpha=0.8)
  plt.savefig("example6.eps")
  plt.show()
  
  
  