pandas - work with rows in subset

import pandas as pd

data = pd.DataFrame({
    'estA': [1., 2., 3., 4.],
    'estB': [5., 6., 7., 8.],
    'estC': [8., 7., 6., 5.],
    'estZ': [0., 3., 0., 1.],
})

#print(data)

Am = data['estA'].mean()
Bm = data['estB'].mean()
Cm = data['estC'].mean()
Zm = data['estZ'].mean()

#print(Am, Bm, Cm, Zm)

for index, row in data.iterrows():
    if row['estZ'] == 0:
        row['estZ'] = Zm/len(data) * (Am/row['estA'] + Bm/row['estB'] + Cm/row['estC'])

print(data)

#-------------------------------------

data = pd.DataFrame({
    'estA': [1., 2., 3., 4.],
    'estB': [5., 6., 7., 8.],
    'estC': [8., 7., 6., 5.],
    'estZ': [0., 3., 0., 1.],
})

#print(data)

Am = data['estA'].mean()
Bm = data['estB'].mean()
Cm = data['estC'].mean()
Zm = data['estZ'].mean()

#print(Am, Bm, Cm, Zm)

subset = data[ data['estZ'] == 0 ]

for index, row in subset.iterrows():
    data['estZ'][index] = Zm/len(data) * (Am/row['estA'] + Bm/row['estB'] + Cm/row['estC'])

print(data)

#-------------------------------------

data = pd.DataFrame({
    'estA': [1., 2., 3., 4.],
    'estB': [5., 6., 7., 8.],
    'estC': [8., 7., 6., 5.],
    'estZ': [0., 3., 0., 1.],
})

#print(data)

Am = data['estA'].mean()
Bm = data['estB'].mean()
Cm = data['estC'].mean()
Zm = data['estZ'].mean()

data['estZ'] = data.apply(lambda row: row['estZ'] if row['estZ'] != 0 else Zm/len(data) * (Am/row['estA'] + Bm/row['estB'] + Cm/row['estC']), axis=1)

print(data)