Change values of column based on another column in dataframe

I have a DataFrame where I want to change the value of the first column if some other columns have been populated.

dataprofile = {'profile_id': [1],'calcrule_id':[2], 'deductible1': [1],'deductible2': [0], 'deductible3':[0],'attachment': [0], 'limit': [2], 'share1':[2],'share2':[0],'share3':[0]}

dfprofile = pd.DataFrame(dataprofile)

#I would like to change the value of calcrule_id only if some other columns have been populated, and would like to nest this.

#What is the best way to go about this?

dfprofile['calcrule_id'] = np.where(dfprofile['deductible1']>=0,'1','1')                       

If deductible 1, limit and attachment have been populated then I would like to change 'calcrule_id' value and so fourth if share has been populated I would like a different value in calcrule_id

I'm not too sure how to go about the if statement if someone could help with an example, thanks in advance .