I'm tracking some products online and creating a data frame based on some data I get from an api and it builds something like this:

```
                          rank    change     usedprice   sold 
2015-11-16 08:34:00     335865  0.159583         17.51  False
2015-11-16 14:37:00     376721  0.121644         17.51  False
2015-11-17 00:10:00     422663  0.121952         17.51  False
2015-11-17 09:52:00     526799  0.246381         17.51  False
2015-11-18 00:10:00     590056  0.120078         17.51  False
2015-11-18 08:50:00     656206  0.112108         17.51  False
2015-11-18 23:10:00     723676  0.102818         17.51  False

```

Each time that product gets searched I return a similar data frame but with new data added on. 

```
                          rank    change     usedprice   sold
2015-11-16 02:34:00     289643       NaN         17.51  False
2015-11-16 08:34:00     335865  0.159583         17.51  False
2015-11-16 14:37:00     376721  0.121644         17.51  False
2015-11-17 00:10:00     422663  0.121952         17.51  False
2015-11-17 09:52:00     526799  0.246381         17.51  False
2015-11-18 00:10:00     590056  0.120078         17.51  False
2015-11-18 08:50:00     656206  0.112108         17.51  False
2015-11-18 23:10:00     723676  0.102818         17.51  False
2015-11-19 11:53:00     818999  0.131721         17.51  False
2015-11-19 20:46:00     840502  0.026255         17.51  False
2015-11-22 12:38:00    1112502  0.323616         17.51  False
2015-11-28 10:32:00    1445509  0.299332         17.51  False
2015-12-03 03:51:00    1795895  0.242396         17.51  False
2015-12-06 21:29:00    2071463  0.153443         17.51  False
2015-12-13 03:26:00    1188341 -0.426328         17.51   True

```

How can I compare the new data frame to the old data frame and only append the rows that do not exists in the original?

Because data is coming from multiple sources, I can not delete the first data frame and just replace it with the new one, sometimes it will only be fed a couple rows of new information that I need to see if that row already exists in the original df and append the row if it does not. 

Seems simple enough, but I just can't seem to find the answer.