Taman Pandan Perdana
Hot Area · Top 3%Pandan Perdana, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
New Condo in PJ Damansara
Pet friendly condo. 10mins to 1Utama
| Road | Price | PSF | Size | Date | Type |
|---|
|
Level 4
|
RM 170,000
|
RM 336
|
506 sqft
|
|
|
|
Level 1
|
RM 145,000
|
RM 287
|
506 sqft
|
|
|
|
Level 2
|
RM 170,000
|
RM 336
|
506 sqft
|
|
New Condo in PJ Damansara
Pet friendly condo. 10mins to 1Utama
New Condo in PJ Damansara
From RM 600,000 · 800 sqft
Pet friendly condo. 10mins to 1Utama
Market Snapshot
RM 170,000
RM 336 psfMedian transaction price
RM 150,000
RM 149 psfMedian transaction price
Pandan Perdana, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
MapsTaman Pandan Perdana in Hulu Langat, Selangor recorded 3 Low-Cost Flat properties subsale transactions between 2021 and 2026, with a median price of RM 170K and a median price per square foot (PSF) of RM 336.
This area contains both residential and commercial properties. View 109 residential properties or 1 commercial properties separately for more focused analysis.
Price remained flat, and PSF growth was PSF remained flat. The median price is RM 170K, with most transactions falling within a stable range of RM 158K to RM 170K, and a typical market range of RM 145K to RM 170K.
Within the Low-Cost Flat category, condominium/apartment dominated the market, with high diversity across multiple property types.
For price per square foot, the median is RM 336, with most transactions between RM 313 and RM 359. The usual range is RM 248.28 to RM 423.78, showing that most units are priced quite close to each other. With an IQR of RM 175.50 and MAD of RM 23, the PSF demonstrates reasonable consistency across the market.
While the area has shown positive growth trends, price variations suggest a more dynamic market. This presents opportunities for investors comfortable with moderate volatility. Significant price variations suggest comparing multiple properties and timing the market carefully. Limited transaction history suggests carefully evaluating comparable sales data.