Comprehensive Pandas toolkit for construction data analysis. Filter, group, aggregate BIM elements, calculate quantities, merge datasets, and generate reports from structured construction data.
SkillScore96Maintained
Automatic
◆Data Analyst pack
Last verified 8/23/2026
What it changes
Passed 23 of 24 test cases with the skill, and 22 of 24 without it.
Without skill92%
With skill96%
Checks it passed that the model alone missed
The result includes reset_index().
1 fixed22 passed either way1 still failing0 broke
Pass-rate lift
+4 pp
Tokens
+246%
Agent turns
0%
Response time
-9%
Model gemini-3.6-flashMeasured 8/23/2026v123 of 24 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
A test case the skill fixed. Same model, same prompt, with and without the skill.
Prompt
Write Python code to group a construction DataFrame by 'Category' using named tuple aggregation syntax to compute 'total_volume' (sum of Volume_m3), 'avg_volume' (mean of Volume_m3), and 'element_count' (count of ElementId), returning a flat DataFrame.
What was checked, without and with the skill
Checked
Without skill
With skill
The aggregation uses tuple-style named aggregation.
Passed
Passed
The result includes reset_index().
Missed
Passed
case-16 · gemini-3.6-flash · 8/23/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md439 linessingle file
Pandas Construction Data Analysis
Overview
Based on DDC methodology (Chapter 2.3), this skill provides comprehensive Pandas operations for construction data processing. Pandas is the Swiss Army knife for data analysts - handling everything from simple data filtering to complex aggregations across millions of rows.
Book Reference: "Pandas DataFrame и LLM ChatGPT" / "Pandas DataFrame and LLM ChatGPT"
"Используя Pandas, вы можете управлять и анализировать наборы данных, намного превосходящие возможности Excel. В то время как Excel способен обрабатывать до 1 миллиона строк данных, Pandas может без труда работать с наборами данных, содержащими десятки миллионов строк."
— DDC Book, Chapter 2.3
Quick Start
import pandas as pd
# Read construction data
df = pd.read_excel("bim_export.xlsx")
# Basic operations
print(df.head()) # First 5 rows
print(df.info()) # Column types and memory
print(df.describe()) # Statistics for numeric columns
# Filter structural elements
structural = df[df['Category'] == 'Structural']
# Calculate total volume
total_volume = df['Volume'].sum()
print(f"Total volume: {total_volume:.2f} m³")
DataFrame Fundamentals
Creating DataFrames
import pandas as pd
# From dictionary (construction elements)