Introduction
Whether you are a buyer, a seller, or a real estate agent, understanding the market dynamics is crucial for making informed decisions. One important but often overlooked metric is the ‘Time on Market’ (TOM). In this blog post, we will delve into what TOM is, its statistics in Westlake Village, CA, and what these numbers mean for you.
What is ‘Time on Market’?
Time on Market represents the duration a property stays listed before it is sold. It’s a vital indicator of market health and property attractiveness.
Key Findings
After removing outliers and performing a more nuanced analysis, we have updated statistics:
- Mean Time on Market: Approximately 95 days
- Median Time on Market: 73.5 days
Real Examples
- Quick Sale: A property was on the market for just 2 days.
- Average Sale: Another property closely aligned with the median ‘Time on Market’ of 73.5 days, staying on the market for 74 days.
- Long Sale: One property stayed on the market for a whopping 455 days!
The Code Behind the Numbers
Transparency is key, so here’s the Python code that calculates the ‘Time on Market’:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# Load the dataset
df = pd.read_csv("path/to/your/dataset.csv")
# Convert 'Entry Date' and 'Closed Date' to datetime format
df['Entry Date'] = pd.to_datetime(df['Entry Date'], errors='coerce')
df['Closed Date'] = pd.to_datetime(df['Closed Date'], errors='coerce')
# Calculate 'Time on Market'
df['Time on Market'] = (df['Closed Date'] - df['Entry Date']).dt.days
# Drop irrelevant or error-prone entries
df = df.dropna(subset=['Time on Market'])
df = df[df['Time on Market'] >= 0]
# Create the visualization
plt.figure(figsize=(10, 6))
sns.histplot(df['Time on Market'], bins=50, kde=True, color='purple', edgecolor='black')
plt.title('Distribution of Time on Market in Westlake Village, CA')
plt.xlabel('Time on Market (Days)')
plt.ylabel('Frequency')
plt.grid(True)
plt.tight_layout()
plt.show()
Visualization
Conclusion
Understanding ‘Time on Market’ can provide invaluable insights for anyone involved in real estate. Whether you are buying, selling, or advising clients, knowing how long properties typically stay on the market can guide your strategies and expectations.