2020kaggle年度调查报告

Top visualization libraries: Matplotlib, Seaborn, Ggplot / ggplot2
Top machine learning frameworks: Scikit-learn, TensorFlow, Keras
Top big data products: PostgresSQL, MongoDB, Microsoft SQL Server
Top BI tools: Tableau, Microsoft Power BI, Data Studio
Top sharing/deploying platforms: Github, Kaggle

云平台使用情况

总结：
１．
The majority of respondents are beginners in data science who are typically in the age of 20-25 from Asia, have graduated from colleges and had 2-3 years of coding experience. Understandably, data science is a relatively new field and usually attracts young talents.
People in data science often begin their careers as data analysts, software engineers, or data scientists.

２．
However, a large number of them would choose to continue their education by pursuing a Master’s degree.
Data science is one of the best-paying jobs nowadays. Fresh data scientists can expect salary starting from 50Kto150K while seniors can make up to $250K. Compensation is likely to increase proportional to your level of expertise.

３．
Machine learning remains to be the hottest trend in data science. While freshers just started to explore machine learning for production or business insight generation, the majority of experts have developed well-established models, and they will continue the work to improve their models and design state-of-the-art machine learning methods.

４．
Python is the key. Learn Python to survive in this world!
As you advance further, you will use more of local development environments than the basic statistical software, so get yourself familiar with them.

５．
Kaggle has been in the top three (1) platforms for deploying data analysis (i.e code sharing), (2) media sources on data science topics, and (3) online data science courses. In addition to Kaggle, Youtube and blogs such as Medium and TowardsDataScience are also great resources for casual learning and networking with people in the field.

链接：
https://www.kaggle.com/kgiangnguyen/alice-in-the-data-science-world