Taiwanese Data Professionals (TDP) was honored to invite Annette Chiu and Paul Gassle to give talks about the integration between data and fashion and a useful python package, dateutil on June 1st.
Annette shared her experiences in using data for improving sales in the fashion industry. Her company was a fast-growing popular yoga clothing brand in the United Kingdom and the United States. As a marketing data analyst, her main job was to analyze the data and understand the market trend. Annette applied math algorithms to calculate the optimization of prices of their products. Competitors play an essential role in determining prices as well. Annette compared the price of similar products with their main competitors and set the retail price. Last but not least, Anette utilized the data about customer returns and analyzed the reason they returned the clothes, which encouraged the company to improve the design of their products.
Paul introduced a useful python package, dateutil, for wrangling data in data and times. Why chose dateutil? There are many different time zones and different transition of Daylight Saving Time around the world. These problems were difficult to observe and solve. Paul provided an interesting case in China. China Standard Time is 8 hours ahead of Coordinated Universal Time (UTC+8). However, the time zone in Urumqi is UTC+6. There were two time zones in China, which was confusing for some data scientists. Other problems of time zone, such as parsing, recurrences, and calendar offsets arose due to the complexity of date and time. Paul worked on dateutil to solve these problems and provided a better package for data scientists.
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