FUTURISTIC GANESH MANDAPS ANALYSIS USING PROC PRINT | PROC MEANS | PROC FREQ | PROC SQL | PROC SORT | PROC TRANSPOSE | PROC REPORT | PROC SGPLOT
/*Creating A Dataset Of Futuristic Mandap In India*/
Step 1: Create futuristic_mandaps dataset
Options Nocenter;
data futuristic_mandaps;
length MandapType $15 Location $20 SpecialFeatures $100;
input MandapType $ Location AttendanceEstimate EnergyUsed InteractionCount
WeatherImpactScore TechCost VisitorSatisfaction EnvironmentalFootprint
SocialMediaEngagement CrowdDensityIndex SpecialFeatures $100.;
datalines;
Virtual Mumbai 7000 500 6000 2 200000 9 2 10000 8 "Immersive 3D VR Storytelling"
Solar Jaipur 3000 1500 0 1 350000 8 1 8000 5 "Solar Powered Lighting and Light Show"
Floating Varanasi 2500 100 0 5 100000 7 3 6000 4 "River Floating Mandap on Ganges"
Drone Bengaluru 1500 300 1200 3 400000 8 2 4000 6 "Drone-Painted Ceiling Artwork"
AI Hyderabad 4000 450 5000 2 250000 9 2 7000 7 "AI Guides and Meditation Suggestions"
BioLum Kerala 1000 200 0 4 300000 10 1 5000 3 "BioLuminescent Plants Glow at Night"
Hologram Delhi 8000 600 0 2 500000 7 1 9000 9 "Life Sized Hologram Projection"
Sandstorm Kutch 1200 350 0 8 150000 8 4 2000 4 "Sandstorm Resistant Materials"
Soundscape Assam 1800 250 4000 3 300000 9 2 4500 6 "Surround Sound Interactive Audio"
Kinetic Chennai 2000 400 2000 3 320000 8 3 3500 5 "Mechanical Moving Sculptures"
;
run;
proc print;run;
Output:
| Obs | MandapType | Location | SpecialFeatures | AttendanceEstimate | EnergyUsed | InteractionCount | WeatherImpactScore | TechCost | VisitorSatisfaction | EnvironmentalFootprint | SocialMediaEngagement | CrowdDensityIndex |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Virtual | Mumbai | Solar Jaipur 3000 1500 0 1 350000 8 1 8000 5 "Solar Powered Lighting and Light Show" | 7000 | 500 | 6000 | 2 | 200000 | 9 | 2 | 10000 | 8 |
| 2 | Floating | Varanasi | "River Floating Mandap on Ganges" | 2500 | 100 | 0 | 5 | 100000 | 7 | 3 | 6000 | 4 |
| 3 | Drone | Bengaluru | "Drone-Painted Ceiling Artwork" | 1500 | 300 | 1200 | 3 | 400000 | 8 | 2 | 4000 | 6 |
| 4 | AI | Hyderabad | "AI Guides and Meditation Suggestions" | 4000 | 450 | 5000 | 2 | 250000 | 9 | 2 | 7000 | 7 |
| 5 | BioLum | Kerala | "BioLuminescent Plants Glow at Night" | 1000 | 200 | 0 | 4 | 300000 | 10 | 1 | 5000 | 3 |
| 6 | Hologram | Delhi | "Life Sized Hologram Projection" | 8000 | 600 | 0 | 2 | 500000 | 7 | 1 | 9000 | 9 |
| 7 | Sandstorm | Kutch | "Sandstorm Resistant Materials" | 1200 | 350 | 0 | 8 | 150000 | 8 | 4 | 2000 | 4 |
| 8 | Soundscape | Assam | "Surround Sound Interactive Audio" | 1800 | 250 | 4000 | 3 | 300000 | 9 | 2 | 4500 | 6 |
| 9 | Kinetic | Chennai | "Mechanical Moving Sculptures" | 2000 | 400 | 2000 | 3 | 320000 | 8 | 3 | 3500 | 5 |
Step 2: Analyze the environmental footprint by Mandap Type
proc means data=futuristic_mandaps mean median min max;
var EnvironmentalFootprint;
class MandapType;
title "Environmental Footprint Statistics by Mandap Type";
run;
Output:
The MEANS Procedure
| Analysis Variable : EnvironmentalFootprint | |||||
|---|---|---|---|---|---|
| MandapType | N Obs | Mean | Median | Minimum | Maximum |
| AI | 1 | 2.0000000 | 2.0000000 | 2.0000000 | 2.0000000 |
| BioLum | 1 | 1.0000000 | 1.0000000 | 1.0000000 | 1.0000000 |
| Drone | 1 | 2.0000000 | 2.0000000 | 2.0000000 | 2.0000000 |
| Floating | 1 | 3.0000000 | 3.0000000 | 3.0000000 | 3.0000000 |
| Hologram | 1 | 1.0000000 | 1.0000000 | 1.0000000 | 1.0000000 |
| Kinetic | 1 | 3.0000000 | 3.0000000 | 3.0000000 | 3.0000000 |
| Sandstorm | 1 | 4.0000000 | 4.0000000 | 4.0000000 | 4.0000000 |
| Soundscape | 1 | 2.0000000 | 2.0000000 | 2.0000000 | 2.0000000 |
| Virtual | 1 | 2.0000000 | 2.0000000 | 2.0000000 | 2.0000000 |
Step 3: Summary of visitor satisfaction and social media engagement
proc sql;
select MandapType, avg(VisitorSatisfaction) as AvgSatisfaction, sum(SocialMediaEngagement) as TotalEngagement
from futuristic_mandaps
group by MandapType
order by TotalEngagement desc;
quit;
Output:
| MandapType | AvgSatisfaction | TotalEngagement |
|---|---|---|
| Virtual | 9 | 10000 |
| Hologram | 7 | 9000 |
| AI | 9 | 7000 |
| Floating | 7 | 6000 |
| BioLum | 10 | 5000 |
| Soundscape | 9 | 4500 |
| Drone | 8 | 4000 |
| Kinetic | 8 | 3500 |
| Sandstorm | 8 | 2000 |
Step 4: Identify most energy efficient mandaps
proc sort data=futuristic_mandaps out=energy_efficient;
by EnergyUsed;
run;
proc print data=energy_efficient (obs=3);
title "Top 3 Most Energy Efficient Futuristic Mandaps";
run;
Output:
| Obs | MandapType | Location | SpecialFeatures | AttendanceEstimate | EnergyUsed | InteractionCount | WeatherImpactScore | TechCost | VisitorSatisfaction | EnvironmentalFootprint | SocialMediaEngagement | CrowdDensityIndex |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Floating | Varanasi | "River Floating Mandap on Ganges" | 2500 | 100 | 0 | 5 | 100000 | 7 | 3 | 6000 | 4 |
| 2 | BioLum | Kerala | "BioLuminescent Plants Glow at Night" | 1000 | 200 | 0 | 4 | 300000 | 10 | 1 | 5000 | 3 |
| 3 | Soundscape | Assam | "Surround Sound Interactive Audio" | 1800 | 250 | 4000 | 3 | 300000 | 9 | 2 | 4500 | 6 |
Step 5: Macro to dynamically analyze waste and safety incidents by Mandap Type
%macro waste_safety_report;
proc means data=futuristic_mandaps mean sum max;
var EnvironmentalFootprint VisitorSatisfaction;
class MandapType;
title "Environmental Footprint and Visitor Satisfaction Summary by Mandap Type";
run;
%mend;
%waste_safety_report;
Output:
The MEANS Procedure
| MandapType | N Obs | Variable | Mean | Sum | Maximum |
|---|---|---|---|---|---|
| AI | 1 | EnvironmentalFootprint VisitorSatisfaction | 2.0000000 9.0000000 | 2.0000000 9.0000000 | 2.0000000 9.0000000 |
| BioLum | 1 | EnvironmentalFootprint VisitorSatisfaction | 1.0000000 10.0000000 | 1.0000000 10.0000000 | 1.0000000 10.0000000 |
| Drone | 1 | EnvironmentalFootprint VisitorSatisfaction | 2.0000000 8.0000000 | 2.0000000 8.0000000 | 2.0000000 8.0000000 |
| Floating | 1 | EnvironmentalFootprint VisitorSatisfaction | 3.0000000 7.0000000 | 3.0000000 7.0000000 | 3.0000000 7.0000000 |
| Hologram | 1 | EnvironmentalFootprint VisitorSatisfaction | 1.0000000 7.0000000 | 1.0000000 7.0000000 | 1.0000000 7.0000000 |
| Kinetic | 1 | EnvironmentalFootprint VisitorSatisfaction | 3.0000000 8.0000000 | 3.0000000 8.0000000 | 3.0000000 8.0000000 |
| Sandstorm | 1 | EnvironmentalFootprint VisitorSatisfaction | 4.0000000 8.0000000 | 4.0000000 8.0000000 | 4.0000000 8.0000000 |
| Soundscape | 1 | EnvironmentalFootprint VisitorSatisfaction | 2.0000000 9.0000000 | 2.0000000 9.0000000 | 2.0000000 9.0000000 |
| Virtual | 1 | EnvironmentalFootprint VisitorSatisfaction | 2.0000000 9.0000000 | 2.0000000 9.0000000 | 2.0000000 9.0000000 |
Step 6: PROC SQL for Mandap Types with highest social media reach and visitor satisfaction
proc sql;
select MandapType, avg(VisitorSatisfaction) as AvgSatisfaction,
sum(SocialMediaEngagement) as TotalReach
from futuristic_mandaps
group by MandapType
having AvgSatisfaction > 8
order by TotalReach desc;
quit;
Output:
| MandapType | AvgSatisfaction | TotalReach |
|---|---|---|
| Virtual | 9 | 10000 |
| AI | 9 | 7000 |
| BioLum | 10 | 5000 |
| Soundscape | 9 | 4500 |
Step 7: Identify Mandaps with high crowd density and recommend sensor deployment
data recommend_sensors;
set futuristic_mandaps;
if CrowdDensityIndex >= 7 and SensorDataAvailable = 'No' then RecommendSensors = 'Yes';
else RecommendSensors = 'No';
run;
proc print data=recommend_sensors;
title "Mandaps Recommended for IoT Sensor Installation";
var MandapType Location CrowdDensityIndex SensorDataAvailable RecommendSensors;
run;
Output:
| Obs | MandapType | Location | CrowdDensityIndex | SensorDataAvailable | RecommendSensors |
|---|---|---|---|---|---|
| 1 | Virtual | Mumbai | 8 | No | |
| 2 | Floating | Varanasi | 4 | No | |
| 3 | Drone | Bengaluru | 6 | No | |
| 4 | AI | Hyderabad | 7 | No | |
| 5 | BioLum | Kerala | 3 | No | |
| 6 | Hologram | Delhi | 9 | No | |
| 7 | Sandstorm | Kutch | 4 | No | |
| 8 | Soundscape | Assam | 6 | No | |
| 9 | Kinetic | Chennai | 5 | No |
Step 8: Visualization of TechCost vs Visitor Satisfaction by Mandap Type
proc sgplot data=futuristic_mandaps;
scatter x=TechCost y=VisitorSatisfaction /
group=MandapType markerattrs=(symbol=circlefilled);
reg x=TechCost y=VisitorSatisfaction;
title "Tech Cost vs Visitor Satisfaction by Mandap Type";
run;
Output:
Step 9: Multi-dimensional analysis with PROC TABULATE
proc tabulate data=futuristic_mandaps;
class MandapType Location;
var AttendanceEstimate TechCost VisitorSatisfaction;
table MandapType,
(AttendanceEstimate TechCost VisitorSatisfaction)* (mean);
title "Mandap Summary Statistics by Type";
run;
| AttendanceEstimate | TechCost | VisitorSatisfaction | |
|---|---|---|---|
| Mean | Mean | Mean | |
| MandapType | 4000.00 | 250000.00 | 9.00 |
| AI | |||
| BioLum | 1000.00 | 300000.00 | 10.00 |
| Drone | 1500.00 | 400000.00 | 8.00 |
| Floating | 2500.00 | 100000.00 | 7.00 |
| Hologram | 8000.00 | 500000.00 | 7.00 |
| Kinetic | 2000.00 | 320000.00 | 8.00 |
| Sandstorm | 1200.00 | 150000.00 | 8.00 |
| Soundscape | 1800.00 | 300000.00 | 9.00 |
| Virtual | 7000.00 | 200000.00 | 9.00 |
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