text: import pandas
  import numpy as np
  import matplotlib
  import matplotlib.pyplot as plt
  from matplotlib.colors import LinearSegmentedColormap
  
  #import matplotlib.colors.Colormap as cm
  path = "/home/shyam8/Sem2/DV/a1-dataset-indian-ocean-consolidated/temp1.csv"
  df = pandas.read_csv(path)
  arr=np.asarray(df)
  print(type(arr[0][0]))
  outlier=arr.max()
  out=np.min(arr)
  sum1=np.float(0)
  maxi=np.float64(outlier)
  print(type(maxi))
  print(type(outlier))
  for i in range(len(arr)):
  	for j in range(len(arr[0])):
  		if(arr[i][j]!=out):
  			if(arr[i][j]<maxi):
  				maxi=arr[i][j]
  print(maxi)
  
  for i in range(len(arr)):
  	for j in range(len(arr[0])):
  		if(arr[i][j]==out):
  			arr[i][j]=np.nan
  '''
  for i in range(len(arr)):
  	for j in range(len(arr[0])):
  		if(arr[i][j]!=out):
  			arr[i][j]=(arr[i][j]/sum1)*255
  		else:
  			arr[i][j]=((out-1)/sum1)*0
  '''
  X=range(len(arr))
  Y=range(len(arr[0]))
  arr_masked = np.ma.array(arr,mask=np.isnan(arr))
  #arr_masked = np.transpose(arr_masked)
  cmap = plt.cm.get_cmap('rainbow')
  cmap.set_under('white',1.)
  #threshold = out
  #arr_masked = np.ma.masked_where(arr < threshold, arr)
  #print(arr_masked)
  #arr = np.ma.masked_greater(arr, maxi)
  #print(arr[0][:10])
  
  #arr=np.transpose(arr)
  #plt.cm(arr,cmap="rainbow")
  plt.pcolor(Y, X, arr_masked, cmap=cmap,vmin=maxi, vmax=outlier)
  plt.colorbar()
  #f = plt.figure()
  #plt.imshow(arr_masked,cmap=cmap)
  #f.canvas.draw()
  plt.show()
  
  