还有一个多月,我工作就满3年了。在职场上,3年是个坎,意味着从初级转到中高级,但前提是能力跟得上工作年限。
我第一份和第二份工作,是做的数据运营,现在这份工作,title是商业分析师。因为专业不是数学、计算机类的,所以相当于转行,但也是理工科,有编程基础,所以相对文科生来说会稍微轻松点,但转行之路并不轻松。
在看到很多想转行的朋友之前,他们会问,比如女生是否适合做数据分析,文科生能不能做好数据分析,数据分析能做什么等等。
[En]
Before seeing a lot of friends who want to change careers, they will ask, for example, whether girls are suitable for data analysis, whether liberal arts students can do data analysis well, what data analysis can do, and so on.
今天我想写的是对过去三年的总结,也是给那些想从事数据分析的同学们的。我希望这会对你从新手到入门三年有所帮助。
[En]
What I want to write today is a summary of the past three years, and it is also for those students who want to engage in data analysis. I hope it will be helpful to you from a rookie to an entry-level three years.
一:开始接触编程
说到开始接触Python应该是2016年12月26日(刚刚考完研),这一天主要做的就是安装Python,当时安装的是Python的原生包,麻烦一些,在配置环境变量的时候一直出错,结果安装了两天,才打印出了Hello World!,其实说真的自己差点放弃。
后来慢慢感受到了乐趣,其中一个很重要的就是先把问题搞清楚,这就需要我们一步一步地把问题分解,然后用搜索工具一步步解决。事实上,在这个过程中,思路会越来越清晰,最终可以解决一半以上的问题,此时问别人可以很有效率。
[En]
Later, I slowly felt the fun, one of which is very important to figure out the problem first, which requires us to decompose the problem step by step, and then use search tools to solve it step by step. In fact, in this process, the train of thought will become clearer and clearer, and finally more than half of the problem can be solved, and it can be very efficient to ask others at this time.
所以当你在学习的时候,你必须经常使用搜索工具(谷歌)。每次搜索时,您都能提高搜索关键字的能力。另一方面,当你向别人寻求建议时,别人可以很容易地问你问题,回答你的问题,为别人着想。事实上,你是在为自己着想,不是吗?
[En]
So when you are learning, you must often use the search tool (Google). Every time you search, you will be able to improve your ability to search keywords. On the other hand, when you ask others for advice, others can easily ask and answer your questions and think of others. In fact, you are thinking about yourself, isn't it?
学习Python时应该注意的问题
如果大家刚接触Python,碰到的第一个问题肯定是安装问题,这其中遇到的麻烦估计就是配置环境变量了(不难,就是一不小心会错);所以建议大家,直接安装Anaconda(官网下载),在安装的过程中,会有类似是否默认设置环境变量,点击是,剩下的默认就可以。
二:对于学习爬虫建议
其实简单来讲爬虫就分为三个部分:
取出要爬取的URL
根据URL请求服务器,下载HTML页面
分析页面内容,找出网页中里的其他URL,继续爬虫直到结束
如果大家打算写一个爬虫程序作为自己找工作的项目实践,推荐使用requests库和Beautiful Soup,再加上QQ浏览器上扩展程序XPath Helper,将会是非常的方便。有一点还请注意,这是一个LINUX下的教程,关于学习爬虫方面,其实涉及到的LINUX命令只有进入一个文件进行编写,复制一个文件,简单的几个命令。
三:对于学习数据分析建议
总结下来主要学习概率统计、Excel、SQL、python基础知识、numpy包、pandas包、matplotlib包。
当我刚开始学习的时候,我的目标是抄袭别人的代码,只要我不报告错误。当时,我有一个很坏的习惯,就是复制代码,从来不用手写代码。总是想学得快,其实没有自己思想的沉淀,不到两天就会忘记代码的逻辑。因此,也建议您自己编写,然后与他人的代码进行比较进行修改。
[En]
When I first started learning, my goal was to copy down other people's code, as long as I didn't report an error. At that time, I had a very bad habit of copying the code and never writing the code by hand. Always want to learn quickly, in fact, without the precipitation of their own thinking, in less than two days will forget the logic of the code. Therefore, it is also recommended that you can write it yourself, and then compare it with other people's code to modify it.
学习编程,真的不怕麻烦,会有错误,但只要能找出错误的原因,一点点积累,肯定是很大的进步。
[En]
Learning programming, really do not be afraid of trouble, there will be mistakes, but as long as you can find out the causes of errors, a little bit of accumulation, it must be a great progress.
道阻且长——几个忠告
技术、业务,想清楚自己想走哪条路线
我是一开始就想走业务,因为我比较想接近前线一些,能够更了解部门业务甚至整个行业的变化。所以职位编制也一直在运营部门。如果是技术路线,编程功底是不能少的,java、python、hive、hadoop之类的是比较主流的。此外就是算法、统计、数学功底也要扎实,计算机和统计专业的比较有优势。
一般来说,大公司要求很高,从技术方向上可以学到很多,待遇也很好。如果一家小公司声称大数据、人工智能等,哈哈,要么是在欺骗用户,要么是在欺骗投资者。
[En]
Generally speaking, large companies are very demanding, and they can learn a lot from the technical direction, and the treatment is also very good. If a small company claims something like big data, artificial intelligence and so on, ha ha, it is either deceiving users or investors.
相信我,只要你选择了互联网,无论你是做技术还是产品,还是运营还是数据分析,你都逃不过中年焦虑。如果你害怕这一点,那就选择传统行业。但只要你把自己的事情做好,就一定没有别的办法,年过三十而不死并不是什么大罪。
[En]
Believe me, as long as you choose the Internet, whether you do technology or product or operation or data analysis, you can't escape middle-aged anxiety. If you are afraid of this, choose the traditional industry. But as long as you do your own thing well, there must be no other way, and it is not a great crime to be over thirty and not to die.
对于初学者来说,做好自己的工作,领导一定要认真对待,及时反馈非常重要。想一想在业余时间提高效率的方法,比如你刚刚制作的表格,是否有更快的方法来实现它,以及图片是否可以做得更清楚、更漂亮。此时,你不会承担部门的数据分析和指导作用,老板也不会太重视你的意见,而是慢慢发光,你的所作所为会让别人眼前一亮,想必领导也会注意到你。
[En]
For beginner children, do a good job of their own work, leaders must be taken seriously, and timely feedback is very important. Think of ways to improve efficiency in your spare time, such as the form you just made, whether there is a faster way to achieve it, and whether the picture can be done more clearly and beautifully. At this time, you will not assume the role of data analysis and guidance of the department, and the boss will not attach great importance to your opinions, but slowly shine, and what you do will brighten the eyes of others, and presumably the leader will notice you.
不要吝啬帮助别人,经常帮助同事,你可能会有新的知识需要学习。你帮了他,下次你再有问题,我相信他不会断然拒绝你的。
[En]
Do not be stingy to help others, often help colleagues, you may have new knowledge to learn. And you helped him, and the next time you have a problem, I'm sure he won't flatly refuse you.
对于中级,这个时候已经开始承接部门的数据和专题分析工作了,对于ppt的撰写,图表的呈现一定要专业,可以学学各大咨询公司的报告,看看别人的报表风格。比如艾瑞咨询的报告,我个人很喜欢这类风格,所以我的图很多也是模仿他的。在ppt或图表上融入公司的主题色(前台或者logo的颜色),会增色不少。
对于先进的,我也在摸索。目前,数据的处理和表达都没有问题,足以应对现有的工作。而是如何从数据中提取信息,改善业务,优化流程。我还在学习这一点。从现有数据的表现来看,向运营商、产品和领导者提出建设性的建议非常具有挑战性,不仅要确保数据准确(这样我们才能得出不偏不倚的结论)。你还必须熟悉商业产品,以及对行业的整体看法。
[En]
For the advanced, I am also groping. At present, there is no problem with the processing and expression of the data, which is enough to cope with the existing work. But how to extract information from the data to improve the business and optimize the process. I am still learning this point. From the performance of the existing data, it is very challenging to put forward constructive suggestions to operators, products and leaders, not only to ensure that the data are accurate (so that we can draw an unbiased conclusion). You also have to be familiar with business products, as well as an overall view of the industry.
路阻且长,行则将至。
文章来源:网络 作者: 网络 版权归原作者所有
以上内容不用于商业目的。如果涉及知识产权问题,请联系小编,我们会立即处理。
[En]
The above content is not used for commercial purposes. If intellectual property issues are involved, please contact the editor and we will deal with them immediately.
Original: https://blog.csdn.net/xuezhangmen/article/details/123865171
Author: 学掌门
Title: 做了三年数据分析,给你的几点建议

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