title: Storage of timeseries data in python
body: <p>I've a amazon price data for around 8.5k products from a period of Feb. 1, 2015 to Oct. 31, 2015. Currently, it is in the form of a dictionary with key as number of days from base date and value as the new price starting that day. Example, here the price is $10 from day 1 and changes to $15 on 45th day, and then changes to $9 on 173rd day and doesn't change after that.</p>
  
  <pre><code>{1:10,
   45:15,
   .
   .
   .
   173:9}
  </code></pre>
  
  <p>What is the best way to store such a timeseries for easy manipulation using python? I would like to perform a lot of aggregations and also would be querying a price on a particular date. Lastly, I would be performing some fixed effect regressions and am confused what would be best way to store this timeseries, so that my programming job becomes comparatively simpler. I could possibly store as table with 273 columns (each for a day) and rows corresponding to 8.5k products. I've been looking at pandas module which can help me do this, but is there a better way? Thanks!</p>