better way to drop nan rows in pandas

Use dropna:

dat.dropna()

You can pass param how to drop if all labels are nan or any of the labels are nan

dat.dropna(how='any')    #to drop if any value in the row has a nan
dat.dropna(how='all')    #to drop if all values in the row are nan

Hope that answers your question!

Edit 1:
In case you want to drop rows containing nan values only from particular column(s), as suggested by J. Doe in his answer below, you can use the following:

dat.dropna(subset=[col_list])  # col_list is a list of column names to consider for nan values.