Fun things to do Pingzhen (TW)

Popular days & hours to visit attractions in Pingzhen Taiwan .

Adjust the filters to find for example your desired busy, quiet, expensive, or highly rated sightseeing spots.

Guangda Park (Park)
No. 10, Guangcheng St, Pingzhen District
4.1

Guangda Park is most popular around 5 PM on Saturdays. It's most quiet on Mondays.

For more info visit the website or checkout Google Maps.

Songwu Park (Park)
No. 151號, Guangtai Rd, Pingzhen District
3.9

Songwu Park is most popular around 7 PM on Tuesdays. Visitors usually stay up to 2 hours here. It's most quiet on Sundays.

For more info visit the website or checkout Google Maps.

Xinjie Riverside Park (Park)
Xizhou St, Zhongli District
4.1

Xinjie Riverside Park is most popular around 10 AM on Mondays. Visitors usually stay up to 1 hour here. It's most quiet on Tuesdays.

Google Maps

新寶公園 (Park)
324, Taiwan, Taoyuan City, Pingzhen District, Lane 70, Xinfu St, 18號
4.1

新寶公園 is most popular around 9 PM on Fridays. It's most quiet on Wednesdays.

For more info visit the website or checkout Google Maps.

壢景町 - 蕃薯藤Café & Eats |町之美文化空間 |有機生活選品 (Other)
320, Taiwan, Taoyuan City, Zhongli District, Yanping Rd, 627號
4.2

壢景町 - 蕃薯藤Café & Eats |町之美文化空間 |有機生活選品 is most popular around 1 PM on Sundays. It's most quiet on Tuesdays.

中壢警察局日式宿舍群於108年9月開放民眾命名票選定名為「壢景町」,建於1941年,當年日本政府透過保甲聯合會向居民募款興建,提供中壢郡役所的警察居住。光復後郡役所改為中壢警分局,繼續作為警眷居住使用。除了其歷史建築特色,也見證過台灣首次民主街頭運動「中壢事件」,2013年公告登錄為桃園市歷史建築,文化局斥資5,300萬元修復,於108年11月15日正式開館營運。

For more info visit the website or checkout Google Maps.

Xinxing Park (Park)
Zhongli District
4.0

Xinxing Park is most popular around 5 PM on Fridays. Visitors usually stay up to 1,5 hours here. It's most quiet on Mondays.

For more info visit the website or checkout Google Maps.

Missing venues? This is a free, but limited tool. Use the BestTime software get more world wide foot traffic data in Pingzhen, Taiwan. Filter points of interest (venues) on foot traffic levels, day, time, dwell time, location, ratings, etc. BestTime provides retail foot traffic and foot traffic analytics.