Twenty shopping streets in Tokyo, Japan, were analyzed based on pedestrian vibrancy and visual information by assessing physical dimensions, objects, shops and quantity of pedestrians and walking speeds. Field survey recorded 12-h periods of a typical weekday by tracking daily variations between July 3rd to August 3rd, 2017 and October 13th to November 10th, 2018. For analysis, Hierarchical Cluster and Discriminant Analyses were performed using the statistical software, SPSS v.24. The study classifies four clusters of shopping streets accordingly to pedestrian vibrancy as eccentric, with large street dimensions and big retailing shops; strong, with variety of specialized daily life stores, balanced, with lower specialized daily life stores, closer residential area and moderate numbers of flower pots; and weakened, with very few shops, residential predominance and higher numbers of flower pots. Findings indicate that larger street dimensions together with specialization of shops, rather than variety or number, are prone to slow walking speeds and larger numbers of people. Also, it was noticeable the connection of number of flower pots with proximity of residential areas. It could be theorized that pedestrian vibrancy correlates inversely to the proximity of residential areas. The closer residential area is the lowest pedestrian vibrancy would be.