BIM Quantity Takeoff
Overview
Quantity Takeoff (QTO) extracts measurable quantities from BIM models. This skill processes BIM exports to generate grouped quantity reports for cost estimation.
Python Implementation
import pandas as pd import numpy as np from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from enum import Enum
class QTOUnit(Enum): """Quantity takeoff measurement units.""" COUNT = "ea" LENGTH = "m" AREA = "m2" VOLUME = "m3" WEIGHT = "kg" LINEAR_FOOT = "lf" SQUARE_FOOT = "sf" CUBIC_YARD = "cy"
@dataclass class QTOItem: """Single QTO line item.""" category: str type_name: str description: str quantity: float unit: str level: Optional[str] = None material: Optional[str] = None element_count: int = 0
@dataclass class QTOReport: """Complete QTO report.""" project_name: str items: List[QTOItem] total_elements: int categories: int generated_date: str
class BIMQuantityTakeoff: """Extract quantities from BIM data."""
# Column mappings for different BIM exports
COLUMN_MAPPINGS = {
'type': ['Type Name', 'TypeName', 'type_name', 'Family and Type', 'IfcType'],
'category': ['Category', 'category', 'IfcClass', 'Element Category'],
'level': ['Level', 'level', 'Building Storey', 'BuildingStorey', 'Floor'],
'volume': ['Volume', 'volume', 'Volume (m³)', 'Qty_Volume'],
'area': ['Area', 'area', 'Surface Area', 'Area (m²)', 'Qty_Area'],
'length': ['Length', 'length', 'Length (m)', 'Qty_Length'],
'count': ['Count', 'count', 'Quantity', 'ElementCount'],
'material': ['Material', 'material', 'Structural Material', 'MaterialName']
}
def __init__(self, df: pd.DataFrame):
"""Initialize with BIM data DataFrame."""
self.df = df
self.column_map = self._detect_columns()
def _detect_columns(self) -> Dict[str, str]:
"""Detect which columns exist in data."""
mapping = {}
for standard, variants in self.COLUMN_MAPPINGS.items():
for variant in variants:
if variant in self.df.columns:
mapping[standard] = variant
break
return mapping
def get_column(self, standard_name: str) -> Optional[str]:
"""Get actual column name from standard name."""
return self.column_map.get(standard_name)
def group_by_type(self, sum_column: str = 'volume') -> pd.DataFrame:
"""Group quantities by type name."""
type_col = self.get_column('type')
qty_col = self.get_column(sum_column)
if type_col is None:
raise ValueError("Type column not found")
if qty_col is None:
# Fall back to count
result = self.df.groupby(type_col).size().reset_index(name='count')
else:
result = self.df.groupby(type_col).agg({
qty_col: 'sum'
}).reset_index()
result['count'] = self.df.groupby(type_col).size().values
result.columns = ['Type', 'Quantity', 'Count'] if len(result.columns) == 3 else ['Type', 'Count']
return result.sort_values('Count', ascending=False)
def group_by_category(self, sum_column: str = 'volume') -> pd.DataFrame:
"""Group quantities by category."""
cat_col = self.get_column('category')
qty_col = self.get_column(sum_column)
if cat_col is None:
raise ValueError("Category column not found")
agg_dict = {}
if qty_col:
agg_dict[qty_col] = 'sum'
if agg_dict:
result = self.df.groupby(cat_col).agg(agg_dict).reset_index()
result['count'] = self.df.groupby(cat_col).size().values
else:
result = self.df.groupby(cat_col).size().reset_index(name='count')
return result.sort_values('count', ascending=False)
def group_by_level(self, sum_column: str = 'volume') -> pd.DataFrame:
"""Group quantities by building level."""
level_col = self.get_column('level')
qty_col = self.get_column(sum_column)
if level_col is None:
raise ValueError("Level column not found")
agg_dict = {}
if qty_col:
agg_dict[qty_col] = 'sum'
if agg_dict:
result = self.df.groupby(level_col).agg(agg_dict).reset_index()
result['count'] = self.df.groupby(level_col).size().values
else:
result = self.df.groupby(level_col).size().reset_index(name='count')
return result
def pivot_by_level_and_type(self) -> pd.DataFrame:
"""Create pivot table: levels as rows, types as columns."""
level_col = self.get_column('level')
type_col = self.get_column('type')
if level_col is None or type_col is None:
raise ValueError("Level or Type column not found")
pivot = pd.crosstab(
self.df[level_col],
self.df[type_col],
margins=True
)
return pivot
def filter_by_category(self, categories: List[str]) -> 'BIMQuantityTakeoff':
"""Filter to specific categories."""
cat_col = self.get_column('category')
if cat_col is None:
raise ValueError("Category column not found")
filtered_df = self.df[self.df[cat_col].isin(categories)]
return BIMQuantityTakeoff(filtered_df)
def filter_by_level(self, levels: List[str]) -> 'BIMQuantityTakeoff':
"""Filter to specific levels."""
level_col = self.get_column('level')
if level_col is None:
raise ValueError("Level column not found")
filtered_df = self.df[self.df[level_col].isin(levels)]
return BIMQuantityTakeoff(filtered_df)
def get_walls(self) -> pd.DataFrame:
"""Get wall quantities."""
cat_col = self.get_column('category')
if cat_col:
walls = self.df[self.df[cat_col].str.contains('Wall', case=False, na=False)]
return BIMQuantityTakeoff(walls).group_by_type()
return pd.DataFrame()
def get_floors(self) -> pd.DataFrame:
"""Get floor/slab quantities."""
cat_col = self.get_column('category')
if cat_col:
floors = self.df[self.df[cat_col].str.contains('Floor|Slab', case=False, na=False)]
return BIMQuantityTakeoff(floors).group_by_type()
return pd.DataFrame()
def get_doors(self) -> pd.DataFrame:
"""Get door quantities."""
cat_col = self.get_column('category')
if cat_col:
doors = self.df[self.df[cat_col].str.contains('Door', case=False, na=False)]
return BIMQuantityTakeoff(doors).group_by_type()
return pd.DataFrame()
def get_windows(self) -> pd.DataFrame:
"""Get window quantities."""
cat_col = self.get_column('category')
if cat_col:
windows = self.df[self.df[cat_col].str.contains('Window', case=False, na=False)]
return BIMQuantityTakeoff(windows).group_by_type()
return pd.DataFrame()
def generate_report(self, project_name: str = "Project") -> QTOReport:
"""Generate complete QTO report."""
from datetime import datetime
items = []
type_col = self.get_column('type')
cat_col = self.get_column('category')
level_col = self.get_column('level')
vol_col = self.get_column('volume')
area_col = self.get_column('area')
mat_col = self.get_column('material')
# Group by type
grouped = self.df.groupby(type_col if type_col else self.df.columns[0])
for type_name, group in grouped:
# Determine primary quantity
qty = 0
unit = QTOUnit.COUNT.value
if vol_col and vol_col in group.columns:
qty = group[vol_col].sum()
unit = QTOUnit.VOLUME.value
elif area_col and area_col in group.columns:
qty = group[area_col].sum()
unit = QTOUnit.AREA.value
else:
qty = len(group)
unit = QTOUnit.COUNT.value
# Get category and material
category = group[cat_col].iloc[0] if cat_col and cat_col in group.columns else ""
material = group[mat_col].iloc[0] if mat_col and mat_col in group.columns else ""
level = group[level_col].iloc[0] if level_col and level_col in group.columns else ""
items.append(QTOItem(
category=str(category),
type_name=str(type_name),
description=str(type_name),
quantity=round(qty, 2),
unit=unit,
level=str(level) if level else None,
material=str(material) if material else None,
element_count=len(group)
))
return QTOReport(
project_name=project_name,
items=items,
total_elements=len(self.df),
categories=self.df[cat_col].nunique() if cat_col else 0,
generated_date=datetime.now().isoformat()
)
def to_excel(self, output_path: str, project_name: str = "Project"):
"""Export QTO to Excel with multiple sheets."""
with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
# Summary by category
self.group_by_category().to_excel(
writer, sheet_name='By Category', index=False)
# Summary by type
self.group_by_type().to_excel(
writer, sheet_name='By Type', index=False)
# Level breakdown
try:
self.pivot_by_level_and_type().to_excel(
writer, sheet_name='Level-Type Matrix')
except:
pass
# Walls
walls = self.get_walls()
if not walls.empty:
walls.to_excel(writer, sheet_name='Walls', index=False)
# Doors and Windows
doors = self.get_doors()
if not doors.empty:
doors.to_excel(writer, sheet_name='Doors', index=False)
windows = self.get_windows()
if not windows.empty:
windows.to_excel(writer, sheet_name='Windows', index=False)
return output_path
Quick Start
Load BIM export
df = pd.read_excel("revit_export.xlsx")
Initialize QTO
qto = BIMQuantityTakeoff(df)
Get quantities by type
by_type = qto.group_by_type() print(by_type.head(10))
Get wall schedule
walls = qto.get_walls() print(walls)
Common Use Cases
- Full QTO Report
qto = BIMQuantityTakeoff(df) report = qto.generate_report("Office Building") print(f"Elements: {report.total_elements}") for item in report.items[:5]: print(f"{item.type_name}: {item.quantity} {item.unit}")
- Level-by-Level Analysis
pivot = qto.pivot_by_level_and_type() print(pivot)
- Export to Excel
qto.to_excel("qto_report.xlsx", "My Project")
Resources
- DDC Book: Chapter 3.2 - Quantity Take-Off