Data on 17,000 National-level Hi-tech Enterprise to Help You Understand the Hi-tech Code of Shenzhen

Country/area: China


Organisation size: Big

Publication date: 11 Nov 2020

Credit: Ye Xiaobin, Lin Hang, Liu Kunya, Xu Yaqiao, Lin Dongwen

Project description:

On the occasion of the opening of the 22nd China Hi-Tech Fair , Shenzhen Evening News published “Data on 17,000 National-level Hi-tech Enterprise to Help You Understandthe Hi-tech Code of Shenzhen”. Through the data on 17,000 national-level hi-tech enterprise, the paper analyzes the“innovation code” of Shenzhen’s high-quality growth. 

Impact reached:

By analyzing the regional distribution, industrial distribution, investment sources and naming characteristics of 17,000 national-level hi-tech enterprise in Shenzhen, this paper fully shows the achievements and experiences of the development of scientific and technological innovation industry in the past 40 years since the establishment of Shenzhen Special Economic Zone, and fully shows the development potential of Shenzhen in the future.

Techniques/technologies used:

We mainly used Python, lllustrator, Photoshop, Excel and other tools to complete this work. We used Python to write code and crawl data, and did data cleaning and data analysis in Excel, and then used lllustrator and Photoshop for data visualization and making charts.

What was the hardest part of this project?

The most difficult part of this project is to crawl and analyze a large amount of data. After obtaining the list of national-level high-tech enterprises from Shenzhen Science and Technology Innovation Committee with Python crawler, we analyzed the data in Excel and obtained important data information, such as the industries and distribution of national-level high-tech enterprises in Shenzhen.

What can others learn from this project?

In China, journalists often get their data from technology companies, but the information on government websites is becoming more and more subdivided and rich. They should pay close attention to the information on various government websites in time to find topics.

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