mirror of
https://github.com/jdejaegh/schlag-score.git
synced 2025-06-26 13:15:39 +02:00
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import json
|
|
import matplotlib.pyplot as plt
|
|
|
|
with open("data_colruyt.json", "r", encoding="utf-8") as f:
|
|
items = json.load(f)
|
|
|
|
def compute_score(item):
|
|
try:
|
|
alcohol = float(item.get("AlcoholVolume", 0))
|
|
amount = item.get("amount", 0)
|
|
if isinstance(amount, dict):
|
|
amount = amount.get("source", 0)
|
|
amount = float(amount)
|
|
price = float(item.get("price", {}).get("basicPrice", 0))
|
|
if price > 0:
|
|
return (alcohol * amount * 100) / price
|
|
except:
|
|
pass
|
|
return 0
|
|
|
|
scored_items = [(compute_score(item), item) for item in items]
|
|
scored_items = [x for x in scored_items if x[0] > 0]
|
|
scored_items.sort(reverse=True, key=lambda x: x[0])
|
|
|
|
rank = 1
|
|
for score, item in scored_items:
|
|
print(f"#{rank} | {score:.2f} | {item.get('LongName', '')} (https://www.colruyt.be/fr/produits/{item.get('commercialArticleNumber')})")
|
|
rank += 1
|
|
|
|
# Distribution plot
|
|
scores = [score for score, _ in scored_items]
|
|
|
|
plt.figure(figsize=(10, 6))
|
|
counts, bins, patches = plt.hist(scores, bins=20, edgecolor='black', alpha=0.7)
|
|
|
|
for count, bin_edge, patch in zip(counts, bins, patches):
|
|
if count > 0:
|
|
plt.text(patch.get_x() + patch.get_width() / 2, count, str(int(count)),
|
|
ha='center', va='bottom', fontsize=8)
|
|
|
|
plt.xlabel('Schlag Score', fontsize=14)
|
|
plt.ylabel('Count of drinks', fontsize=14)
|
|
plt.title('Schlag Score Distribution', fontsize=16)
|
|
plt.xticks(bins, [f"{b:.0f}" for b in bins])
|
|
plt.xlim(left=0)
|
|
plt.ylim(bottom=0)
|
|
plt.gca().spines['top'].set_visible(False)
|
|
plt.gca().spines['right'].set_visible(False)
|
|
plt.tight_layout()
|
|
plt.savefig("score_distribution.png", dpi=300)
|