Pandas: Filling random empty rows with data

I have a dataframe with several currently-empty columns. I want a fraction of these filled with data drawn from a normal distribution, while all the rest are left blank. So, for example, if 60% of the elements should be blank, then 60% would be, while the other 40% would be filled. I already have the normal distribution, via numpy, but I'm trying to figure out how to choose random rows to fill. Currently, the only way I can think of involves FOR loops, and I would rather avoid that.

Does anyone have any ideas for how I could fill empty elements of a dataframe at random? I have a bit of the code below, for the random numbers.

data.loc[data['ColumnA'] == 'B', 'ColumnC'] = np.random.normal(1000, 500, rowsB).astype('int64')