Nowadays, the competition in the workplace is becoming more and more fierce. If you don't learn one or two new skills and keep your knowledge updated, it's easy for your younger generation to surpass you. Some people choose to learn a foreign language, others choose to learn the ability to deal with people in the workplace.
If your job needs to process data, believe me, Python will definitely be a stepping stone to your promotion and salary increase. Why? Because it is efficient. Let's look at the recruitment information of a senior data analyst with an annual salary of 24w-48w. The following four abilities are more valued by employers:
After careful combing, you will find that even if you are not a data analyst, having these four abilities can add points for yourself in the workplace. Imagine that when an e-commerce promotion ends, others spend a lot of time sorting out the data, and you have more energy to analyze the positioning problem, so you can make a better-looking interactive chart. Business analysis, you pull a lot of data and make charts by hand, which is not as efficient as a few lines of Python code. Let's analyze them one by one.
1, business insight and execution, business insight and execution, the popular point is how to obtain effective information from massive information.
Python can use MySQLdb library to connect to the database, pandas and matplotlib to clean up and analyze, pyecharts to interactively visualize, numpy and sklearn to model, and even pyinstaller can package the workflow to colleagues. * * * The same effect ...
Call the matplotlib library to quickly sort out the data and draw with a few lines of code.
When the tools are more efficient, there is more time to deeply understand and analyze the business.
2. Communication skills
Python can also improve communication skills?
Data analysts belong to the business side and have long been in contact with the company's projects and customer needs. Technical parties generally only care about the realization of product functions. Analysts who master Python will have a better understanding of the pain points in both business and technology.
3.Python and SQL
To deal with massive data, only Excel is uneconomical, so most data analysts need SQL skills.
Getting started with SQL language is very simple. After mastering the functions of accessing data and cleaning up basic data, you can start working. Junior analysts may bring a few numbers to the local area for analysis, and efficient data analysts will use Python to connect to the database for analysis, making the workflow more efficient.
Query database documents using Python tool library pymongo
4. Initiative and logic Initiative and logic are metaphysics. People in the workplace will say that they have the initiative, but the question is how can the boss feel your initiative? like ...
When the conversion rate data is low, quickly search the data to find out the reason, and even write an automatic early warning script in Python to accurately express it to front-line business personnel, instead of saying "I think" when the boss asks you; When the company's new business has not yet taken shape, use Python to collect and sort out effective data and establish a visual index system to guide the business, instead of the boss asking you and saying "I think"; Active learning, actively looking for new ways to improve efficiency in the solidified data workflow, such as finding that colleagues are still copying and pasting repetitive work, and using Python to help colleagues write a script merge file. Although the boss won't ask about this detail, initiative and logic can only be shown because of a person's strong ability.
Using Python to write gadgets, you can merge 9 12 Excel tables in a few minutes.
To sum up, it is impossible to be a "senior" data analyst. Only by constantly learning and thinking can we be top notch.