Wei and his Daddy Lab

Unlike counterparts in Western countries, social businesses in China are still in their infancy. The distinction between non-profits/social philanthropies and social businesses has been introduced to the public only in recent years. The China Social Enterprise and Impact Investing Forum (CSEIF) created in September 2014 has been actively uniting all the social entrepreneurs in China and organizing events to promote their growth. I was particularly interested in one of them — Wenfeng Wei, the founder of Daddy Lab.

Before founding Daddy Lab, Wei was the General Manager of a private firm (which provides assessment services on the safety and toxicological…

Ant Financial’s logo

Strict sanitary measures resulting from the COVID-19 have forced businesses to operate online to the largest extent possible. In China, the switch from offline to online was greatly facilitated by platform-like tech giants who have penetrated almost every aspect of Chinese urban life. From the financial perspective, businesses of all sizes in China have been empowered to continue to make smooth transactions with their customers thanks to innovative FinTech companies. Billions of nonbank online payments were generated on a daily basis (the figure had already reached 720 billion worthy of US$383 trillion in 2019, well before the COVID-19, averaging around…

In its simplest form, auction ads delivery can be regarded as a classic constrained optimization problem. There is a well-defined objective function (can be multiple functions under some circumstances) and a whole bunch of constraints. What we need to do is to maximize (or minimize) the objective function with the constraints being satisfied.

We shall first look into the objective function. The ultimate goal of advertising, be it online or offline, is to efficiently connect ads with people who are really interested in the products/services being advertised and are willing to take the desired actions like downloads or purchases. This…

(a panda enjoying his/her time)

I’ve frequently encountered operations that are not well supported by the original pandas package and every time when this happens I have to spend some time looking for clues on StackOverflow . Therefore I decided to make this collection for self-reference and of course for anyone who might find it helpful! (I will keep adding new codes! )

I. Creating a DataFrame

  1. From existing files:

Please refer to this link:pandas Input/Output Reference

Input file types supported by Pandas: .csv, .xlsx, .zip, .txt, .json, .xml, .html, images, Hierarchical Data Format, .pdf, .docx, .mp3, .mp4, .sql

2. Creating from a dictionary:

Honghao Yu

Product Manager at TikTok | MSc. Data Science for Business at École Polytechnique & HEC Paris

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