Python is an object-oriented, interpreted computer programming language with a rich and powerful library. It has become the third largest language after Java and C++. Compared with other languages, its characteristics are: easy to learn, portable, extensible, embeddable, rich libraries, free and open source, etc. Python has low difficulty and is very suitable for Beginner programmers .
Simply put, among the current programming languages, Python has the highest level of abstraction and is the closest to natural language. It is very easy to get started. Python can help you better understand programming.
The new Tiobe programming language ranking list was released in October. Python is still ahead of its old rivals Java and C, firmly ranking first on the list, and the lead is huge .
The list data is objective and true. There are more and more users of Python now, far exceeding other languages. Its absolute advantage in web crawling is an important reason for Python's popularity.
This is an era of Internet of Everything. People's behavior in the online world generates a large amount of data, which has great commercial value . As the best and fastest data collection technology, the importance of crawlers is self-evident.
In recent years, the industry's demand for crawler technology services has been skyrocketing , and now demand exceeds supply. The unbalanced relationship between supply and demand has made the price of crawler services extremely high . Therefore, many people in the Python circle, including myself, do Python side jobs in their spare time to make extra money.
Data analysis and big data visualization have become increasingly popular in recent years, and new business models based on big data have spawned a large number of successful Internet giants. The general environment requires all positions to work around data, and Python data analysis has become an essential skill for job promotion and salary increase, and the annual salary of excellent data analysts can reach 40W+ .
Although the demand is huge, there are many orders, and the remuneration is very generous, not everyone can make this money. To take on private work with crawlers, you need to have sufficient technical reserves . If you don’t have enough skills, you won’t be able to receive orders.
Therefore, whether they are professionals in sales, marketing, operations, planning, products, finance, legal affairs, human resources, etc. who want to get a promotion or salary increase, or they are graduates or career changers who want to be professional mathematicians, many people have begun to learn on their own. Python data analysis.
Python is considered the basic language for artificial intelligence and machine learning, and data science and artificial intelligence have a close intersection. Therefore, it is not surprising that Python is regarded as the most widely used language in data science.
Now let us review the various steps in the process of solving data science problems to further understand the role Python plays in it.
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Data collection and cleaning
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Data exploration
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Data modeling
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Data visualization and interpretation
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Data collection and cleaning
With Python, you can load data in a variety of different formats, such as CSV (comma-separated values), TSV (tab-separated values), or JSON from the web.
Whether you want to load SQL tables directly into your program, or you need to crawl website information, Python can help you complete these tasks easily: you can use the PyMySQL package for the former task, and the BeautifulSoup package for the latter task.
PyMySQL allows you to easily connect to MySQL databases, execute queries, extract data, etc. BeautifulSoup can help you read XML and HTML type data. After extracting and replacing values, you may also want to deal with missing and meaningless values during the data cleaning phase.
Additionally, if you have trouble processing a particular data set, you can search the Internet for the name of the data set followed by "Python" and you may be able to find a solution.
(Crawling Maoyan reviews and ratings, and analyzing the reasons for the low score of the movie)
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Web crawler/crawling : Python's beautifulsoup and Scrapy are more mature and powerful. Combined with django-scrapy, we can quickly build a customized crawler management system.
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Connecting to the database : Python only uses sqlachemy through ORM. One package solves various database connection problems and is widely used in production environments. Because Python supports placeholder operations, it is more convenient when splicing SQL statements.
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Content management system : Based on Django, Python can quickly establish a database and backend management system through ORM.
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API construction : Through Tornado, a standard network processing library, Python can also quickly implement lightweight APIs.
According to a report by an authoritative data research institution, China's data talent gap may reach 2 million by 2025 ; statistics from the Data Analysis Department of the China Business Council show that the gap in China's basic data analysis talents will reach 10 million+ in the future .
Let's take a look at the current recruitment requirements and salary packages for enterprise data analysts, and it doesn't disappoint.
It goes without saying that Python data analysts may be the most scarce and lucrative profession in the next five years.
Python has been extremely popular in recent years and is widely used. For example: crawlers, data analysis, scientific computing, artificial intelligence, Python can all be competent.
In Internet companies, many people like to use Python to complete automated office work, form processing, data analysis and other tasks . Learning Python makes your work more efficient! Perhaps because of this universal attribute, using Python for data analysis has become more and more popular, and has become a basic skill and a necessary skill for all professionals .
Why do companies attach so much importance to data analysis? Nowadays, more and more companies are focusing on data-driven and using data to speak. This is because by refining complex data, the key points can be presented to us more intuitively and clearly.
McKinsey once said: " Data has penetrated into every industry and business function area today and has become an important production factor . People's mining and application of massive data heralds the arrival of a new wave of productivity growth and consumer surplus. "
[Following the trend of the times, I have compiled a lot of Python learning materials here and uploaded them to the CSDN official. Friends in need can scan the QR code below to obtain them]
1. Study Outline
2. Development tools
3. Python basic materials
4. Practical data
