[USER (data scientist)]: What is the distribution of property prices in Flemington, Australia? Show me histogram plot of property prices to visualize the distribution. Please generate a DataFrame to analyze the property ages in Flemington, including mean, median, first quartile, and third quartile values, and identify historical buildings that could be renovated for sustainability, storing the analysis and identified buildings for renovation in pickle files.

My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd
import pickle

melbourne_housing = pd.read_csv("melb_data.csv")

# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]
</code1>
# YOUR SOLUTION END:

print(f"Mean property age: {mean_age:.2f} years")
pickle.dump(mean_age,open("./pred_result/mean_age.pkl","wb"))

print(f"Median property age: {median_age:.2f} years")
pickle.dump(median_age,open("./pred_result/median_age.pkl","wb"))

print(f"First quartile: {first_quartile:.2f} years")
pickle.dump(first_quartile,open("./pred_result/first_quartile.pkl","wb"))

print(f"Third quartile: {third_quartile:.2f} years")
pickle.dump(third_quartile,open("./pred_result/third_quartile.pkl","wb"))

print("\nBuildings that could be renovated for sustainability:")
print(buildings_to_renovate[['Suburb', 'Address', 'YearBuilt']])
pickle.dump(buildings_to_renovate,open("./pred_result/buildings_to_renovate.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I can help you with that.
