Two points need to be declared:
- This is not a questionnaire, but a statistical report based on user data analysis.
- It’s not an advert, and I’m not getting paid for it.
Before starting to do data analysis, nuggets gave me an intuitive feeling that it was a community that shared front-end knowledge and had a lot of Android technology, but today I have a data as a reference, and the feeling is more direct.
The most popular language in the community is JavaScript, with nearly 30 percent of posts being about JavaScript, while Java is a surprising second place as the two main directions for Android and back-end development.
Analysis of the reason may be related to the technical background of the founding team of Denver gold. The CEO Yin Ming was a front-end developer, and the back-end mainly relied on a cloud service. It is estimated that a large number of like-minded front-end seed users may have gathered in the early stage of the website to share content in the community.
Swift is well ahead of Objective-C, which is pretty close to TIOBE’s ranking trends. I’m sure objective-C will shrink further, and Swift will be more likely to be used for new projects in addition to legacy systems.
Python is a well-deserved 4th place in the list as an all-around warrior for the Web, crawlers, data analytics, quantitative trading, machine learning, and AI. Surprisingly, there is no C# on the list, as Microsoft has gradually faded from the limelight.
The front end has been hot for several years, from the Web front end to the back end Node.js, and then to the mobile end ReactNative, js seems to run through the cloud to the terminal, has a tendency to dominate the world. Let’s see what frame they’re playing with.
JQuery’s share is falling, but her mission is done. Vue. Js, React. Js and angular. js form a three-way rivalry. Of course, there are all kinds of small shrimp millet, front-end ecology can be described as a mixed bag. The question is, can you learn from new technologies and frameworks? My advice is to learn the basics, pick a market good study, technology is interlinked.
Android developers in the community are the largest in terms of visits, with Android attracting more than twice as many visits as iOS. It’s no surprise that Android phones account for 86% of the market, according to IResearch. A side example: When I talked to a friend who was working on the Java backend about nuggets, he said he had never heard of nuggets. So nuggets operations students to force, DORA point back-end developers to play.
What kind of articles do you like the most? I analyzed the top 100 most-read posts, and those that talked about interviews, tutorials, wechat development, free, resources, and guides were more popular. So if you’re a writer and need to write 10K + reading articles, consider these areas.
Beware of trypophobia! There is a “full stack” in the bottom left corner. It seems that the concept of “full stack” is basically out of our sight. It shows that we are more pragmatic and not just Shouting slogans to call ourselves “full stack”.
I don’t know if you care how these diagrams are technically implemented, but here’s a quick idea.
The primary task of data analysis is to get data. If you open the browser and press F12, you will know how to get data by doing a little bit of analysis. Whether it is using crawlers or other methods, it is the means to get data. After data is stored locally, it is cleaned to facilitate statistics. In this case, you need to use numpy, PANDAS, Matplotlib, and Plotly to analyze, calculate, and visualize data. The last picture is wordcloud display by wordcloud after jieba word segmentation.
I was trying to figure out how many female developers there were, but unfortunately there’s no way to get the gender of the user, and I think it would be really interesting if we could use machine learning to figure out whether a user is male or female.
All data analysis is done in the environment of Jupyter Notebook, so you can see the detailed process of data statistics for each step. The complete code can be obtained by answering “data” on the official account. Would you like to have an introduction to Python data analysis next time? Please leave a message
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