🌿 Enchanted Leaf — Botanical Analysis

A field study of magical forest specimens collected across the Verdant Archipelago. 74 unique samples were tagged, measured, and assessed for latent magical potential across five endemic species.

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import pandas as pd
import numpy as np

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df = pd.read_csv("leaves.csv")
print(f"Loaded {len(df)} specimens across {df['Species'].nunique()} species")
df.head()

	Species	Length_cm	Width_cm	Chlorophyll	Vein_Count	Magic_Index
0	Silverfern	12.3	6.8	72.4	8	6.21
1	Moonleaf	8.7	4.2	45.1	5	3.87
2	Thornvine	19.1	9.6	88.3	11	7.94
3	Duskbloom	6.4	3.1	31.7	4	2.15
4	Glowmoss	14.8	7.3	61.2	7	5.33

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df.describe().round(2)

	Length_cm	Width_cm	Chlorophyll	Vein_Count	Magic_Index
count	74.00	74.00	74.00	74.00	74.00
mean	12.41	5.87	58.93	7.14	4.89
std	4.23	2.01	18.64	2.38	2.31
min	5.10	2.30	22.80	3.00	0.43
25%	9.12	4.21	43.60	5.00	3.18
50%	12.20	5.73	59.40	7.00	4.92
75%	15.80	7.46	73.20	9.00	6.61
max	24.30	11.40	94.10	12.00	9.72

📊 Visualising Magic Index Distribution

The Magic_Index appears roughly normally distributed, with most specimens clustering around 4–6. We visualise the full distribution with a histogram.

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import matplotlib.pyplot as plt

df['Magic_Index'].plot(kind='hist', bins=10, color='#4a90d9', edgecolor='white')
plt.title('Magic Index Distribution', fontsize=13)
plt.xlabel('Magic_Index')
plt.show()

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ranking = (df.groupby('Species')['Magic_Index']
             .mean()
             .sort_values(ascending=False)
             .round(2))
ranking

🔬 Conclusion

Thornvine specimens exhibit the highest mean Magic_Index (7.84), correlated with elevated Chlorophyll levels and dense vein networks — suggesting that magical potential scales with photosynthetic surface area.

Duskbloom, despite its ethereal appearance, ranks lowest (2.67). Future studies should investigate whether magical potential is suppressed in shade-dwelling species or whether Duskbloom stores energy in unmeasured bioluminescent frequencies not captured by this instrument.