45 lines
1.8 KiB
Python
45 lines
1.8 KiB
Python
#!/usr/bin/env python3
|
|
"""Generate new data and display sample showing upward trend"""
|
|
import subprocess
|
|
import pandas as pd
|
|
|
|
# Run data generator
|
|
result = subprocess.run(['python3', 'Data Gen.py'], capture_output=True, text=True)
|
|
print(result.stdout)
|
|
if result.stderr:
|
|
print("Errors:", result.stderr)
|
|
|
|
# Load and display trend analysis
|
|
df = pd.read_csv('organization_happiness_study_data.csv')
|
|
df['Habits_Count'] = (
|
|
(df['Calendar_Adherence'] == 'Yes').astype(int) +
|
|
(df['Cleanliness_Adherence'] == 'Yes').astype(int) +
|
|
(df['Punctuality_Adherence'] == 'Yes').astype(int)
|
|
)
|
|
|
|
intervention = df[df['Group'] == 'Intervention']
|
|
control = df[df['Group'] == 'Control']
|
|
|
|
print("\n" + "="*70)
|
|
print("UPWARD TREND ANALYSIS")
|
|
print("="*70)
|
|
|
|
print("\n[INTERVENTION GROUP] - Should show upward trend")
|
|
early_int = intervention[intervention['Day'] <= 7]
|
|
late_int = intervention[intervention['Day'] >= 24]
|
|
print(f"Days 1-7: Avg Happiness = {early_int['Happiness'].mean():.2f}")
|
|
print(f"Days 24-30: Avg Happiness = {late_int['Happiness'].mean():.2f}")
|
|
print(f"GROWTH: +{late_int['Happiness'].mean() - early_int['Happiness'].mean():.2f} points\n")
|
|
|
|
print("[CONTROL GROUP] - Should show flat/random pattern")
|
|
early_ctl = control[control['Day'] <= 7]
|
|
late_ctl = control[control['Day'] >= 24]
|
|
print(f"Days 1-7: Avg Happiness = {early_ctl['Happiness'].mean():.2f}")
|
|
print(f"Days 24-30: Avg Happiness = {late_ctl['Happiness'].mean():.2f}")
|
|
print(f"CHANGE: {late_ctl['Happiness'].mean() - early_ctl['Happiness'].mean():+.2f} points\n")
|
|
|
|
print("[HABIT CORRELATION] - More habits = Higher happiness")
|
|
for habits in range(4):
|
|
subset = intervention[intervention['Habits_Count'] == habits]
|
|
if len(subset) > 0:
|
|
print(f"{habits} habits/day: Avg Happiness = {subset['Happiness'].mean():.2f} ({len(subset)} observations)")
|