title: Data Compression
body: <p>i have a task to compress a stock market data somehow...the data is in a file where the stock value for each day is given in one line and so on...so it's a really big file.</p>
  
  <p>Eg, <br>
  123.45 <br>
  234.75 <br>
  345.678 <br>
  889.56 <br>
  .....<br></p>
  
  <p>now the question is how to compress the data (aka reduce the redundancy) using standard algorithms like Huffman or Arithmetic coding or LZ coding...which coding is most preferable for this sort of data??...</p>
  
  <p>I have noticed that if i take the first data and then consider the difference between each consecutive data, there is lot of repetition in the difference values...this makes me wonder if first taking these differences, finding their frequency and hence probalility and then using huffman coding would be a way??...</p>
  
  <p>Am i right?...can anyone give me some suggestions.</p>