October - December 2019
Case Study: Tracking Footsteps
Tracking Footsteps is a case study that aims to study how a collective of receipts/records can be understood to formulate patterns and insights into a person’s lifestyle, daily routines and frequent locations. Collected for a month, information from these receipts are extracted, organised and then visualised via a map plotting table, enabling information to be represented in location, date, time and kind.
Methodology
Collected for a month, information from these receipts are extracted, organised and then visualised via a map plotting table, enabling information to be represented in location, date, time and kind. Categorised into 2 sections, the study is focussed on articulating user habits and movement, in efforts to find out the patterns and insights of the user.
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Sources
Statistic information is collated from an anonymous source via legal channels
Above Visualisation on a user's movements throughout a period of a month. Conducted in October 2019.
Based on common attainable data sets, the data can be translated into specific data pointers that relate to its sub-sets. For instance, all sub-sets utilizes the location data from the main data sets to provide for the user's Spending Habits, or Frequented Locations, per se.
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Ultimately, data is communicated into statistics that implore the hacker to better understand the user's patterns and behaviours.
Spending Habits (Instances x Location)
By representing the location data towards the value, the visualisation depicts the spending patterns of the user, where a large group of transactions appear to the in frequents areas of the Orchard - Bugis area and the Bishan - Thomson area.
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On the other hand, a number of purchases also occurred in the east, central area and slightly at the northern area. From this visualisation, it can be inferred that the user regularly transacts in the central and southern parts of Singapore
$625.6
Total Spent in a Month
x163
Times Spent via Card/Contactless Payment