human
Solve the following python programming problem given the following code:
def _lookup_parking_cfg(self, form, parking_config, df, only_built = True, pass_through = None) : 
    dev_info = self.dev_d [(form, parking_config)] 
    cost_sqft_col = np.reshape (dev_info.ave_cost_sqft.values, ((- 1), 1)) 
    cost_sqft_index_col = np.reshape (dev_info.index.values, ((- 1), 1)) 
    parking_sqft_ratio = np.reshape (dev_info.parking_sqft_ratio.values, ((- 1), 1)) 
    heights = np.reshape (dev_info.height.values, ((- 1), 1)) 
    df = df.copy () 
    c = self.config 
    df ['weighted_rent'] = np.dot (df [c.uses], c.forms [form]) 
    df ['max_far_from_heights'] = ((df.max_height / c.height_per_story) * c.parcel_coverage) 
    if ('max_dua' in df.columns) : 
        assert ('ave_unit_size' in df.columns) 
        df ['max_far_from_dua'] = ((((df.max_dua * (df.parcel_size / 43560)) * df.ave_unit_size) / self.config.building_efficiency) / df.parcel_size) 
        df ['min_max_fars'] = df [['max_far_from_heights', 'max_far', 'max_far_from_dua']].min (axis = 1) 
else : 
        df ['min_max_fars'] = df [['max_far_from_heights', 'max_far']].min (axis = 1) 
if only_built : 
        df = df.query ('min_max_fars > 0 and parcel_size > 0') 
fars = np.repeat (cost_sqft_index_col, len (df.index), axis = 1) 
    fars [(fars > (df.min_max_fars.values + 0.01))] = np.nan 
    heights = np.repeat (heights, len (df.index), axis = 1) 
    fars [(heights > (df.max_height.values + 0.01))] = np.nan 
    building_bulks = (fars * df.parcel_size.values) 
    building_costs = (building_bulks * cost_sqft_col) 
    total_costs = (building_costs + df.land_cost.values) 
    building_revenue = ((((building_bulks * (1 - parking_sqft_ratio)) * c.building_efficiency) * df.weighted_rent.values) / c.cap_rate) 
    profit = (building_revenue - total_costs) 
    profit = profit.astype ('float') 
    profit [np.isnan (profit)] = (- np.inf) 
    maxprofitind = np.argmax (profit, axis = 0) 
    def twod_get(indexes, arr) : 
        return arr [(indexes, np.arange (indexes.size))].astype ('float') 
outdf = pd.DataFrame ({ 
      ...

    
    

    Fix the buggy line: outdf ['non_residential_sqft'] = ((outdf.building_sqft * c.building_efficiency) * resratio)
assistant
#Here is Python program to fix the buggy line: outdf ['non_residential_sqft'] = ((outdf.

outdf ['non_residential_sqft'] = ((outdf.building_sqft * c.building_efficiency) * nonresratio)