[USER (data scientist)]: Hey, I have this Melbourne housing dataset and I need some help analyzing it. 
 
[YOU (AI assistant)]: Sure, I'd be happy to help! What kind of analysis are you looking to do? 
 
[USER (data scientist)]: I want to find out how many affordable houses, townhouses, and units were sold in the last 5 years. But first, let's make sure the 'Date' column is in the right format. Please load the 'melb_data.csv' file into a DataFrame and convert the 'Date' column to datetime format, then save the updated DataFrame to a pickle file.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import matplotlib.pyplot as plt
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(melbourne_housing)

# save data
pickle.dump(melbourne_housing,open("./pred_result/melbourne_housing.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Alright, let's start by converting the 'Date' column to datetime format. You can use this code: 
