I'm new to data science and trying to do some data wrangling with python 2.7 in iPython notebook. A tutorial I was following for my first project asked me to replace all NaN intputs with 0 or 1. But I'd like to consider another approach where I can 1st look at the count for the rows with non-numerical values corresponding to all rows having credit_history as NaN...I'm new to data science and trying to do some d