How to delete a row in a Pandas DataFrame and relabel the index?

Question

I am reading a file into a Pandas DataFrame that may have invalid (i.e. NaN) rows. This is sequential data, so I have row_id+1 refer to row_id. When I use frame.dropna(), I get the desired structure, but the index labels stay as they were originally assigned. How can the index labels get reassigned 0 to N-1 where N is the number of rows after dropna()?

Answer 1

In addition to an accepted answer:

You should also use inplace=True as well:

df.reset_index(drop=True, inplace=True)