#data
d = {'year': {0: 2016,
  1: 2016,
  2: 2016,
  3: 2016,
  4: 2017,
  5: 2017,
  6: 2017,
  7: 2017,
  8: 2018,
  9: 2018,
  10: 2018},
 'id': {0: 1015.0,
  1: 1016.0,
  2: nan,
  3: nan,
  4: 1035.0,
  5: 1036.0,
  6: nan,
  7: nan,
  8: 1005.0,
  9: nan,
  10: nan}}

# list of years
years = [2016,2017,2018]

# create dataframe
df = pd.DataFrame(d)

# create list that I will append data frames too
l = []

for x in years:
    # create a dataframe for each year
    df1 = df[df['year']==x].copy()
    # fill nans with max value plus 1
    df1['id'] = df1['id'].fillna(lambda x: x['id'].max() + 1)
    # add dataframe to list
    l.append(df1)
# concat list of dataframes
final = pd.concat(l)

df1['id'] = df1['id'].apply(lambda x: x['id'].fillna(x['id'].max() +1))

TypeError: 'float' object is not subscriptable