Prima Pelangi

Perdana Botanical Gardens, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

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From
RM600K
Size
800 sqft

Property Transactions

10 subsales found

Median
RM340,000
PSF
RM313
Price Size
Period
transactions middle 50% (P25–P75)
RM310,000
Level 13
1,163 sqft RM267 PSF
RM400,000
Level 17
1,141 sqft RM351 PSF
RM380,000
Level 6
1,023 sqft RM372 PSF
RM320,000
Level 13
1,066 sqft RM300 PSF
RM400,000
Level 11
1,163 sqft RM344 PSF
RM345,000
Level 15
1,119 sqft RM308 PSF
RM410,000
Level 7
1,163 sqft RM353 PSF
RM325,000
Level 12
1,023 sqft RM318 PSF
RM300,000
Level 12
1,066 sqft RM282 PSF
RM335,000
Level 6
1,119 sqft RM299 PSF
Legend Recent Highest Price Highest PSF

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Market Snapshot

Residential

RM340,000

RM313 psf

Median transaction price

Prima Pelangi
© OpenStreetMap · CARTO

Perdana Botanical Gardens, 50480 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia

Maps

Prima Pelangi in Kuala Lumpur, Kuala Lumpur recorded 10 subsale transactions in 2022, with a median price of RM340K and a median price per square foot (PSF) of RM313.

This area consists exclusively of residential properties, with no commercial listings recorded.

Price remained flat, and PSF growth was PSF remained flat. The median price is RM340K, with most transactions falling within a stable range of RM301K to RM379K, and a typical market range of RM305K to RM375K.

Most transactions involved condominium/apartment, with minimal variety in property types.

The median PSF stands at RM313, with core pricing between RM281 and RM345. Market pricing typically extends from RM286.51 to RM339.51, reflecting moderate variation in unit pricing. With an IQR of RM53.00 and MAD of RM32, the PSF demonstrates reasonable consistency across the market.

Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. The consistent property type and stable pricing make it easier to assess value and compare trends. Limited transaction history suggests carefully evaluating comparable sales data.