better way to drop nan rows in pandas

To expand Hitesh's answer if you want to drop rows where 'x' specifically is nan, you can use the subset parameter. His answer will drop rows where other columns have nans as well

dat.dropna(subset=['x'])

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.