Shulou(Shulou.com)06/02 Report--

In every enterprise, various departments will produce certain data. at present, all kinds of data play a vital role in the production and operation of enterprises.

Data has become indispensable information for almost all business activities, such as production, operation, strategy and so on.

Correct data analysis can help enterprises to make wise business decisions, the data is like the eyes of business operators, through the data can reflect business problems, just like the helmsman relies on navigation.

How is the data analyst trained?

In fact, to put it bluntly, data analysis is a technology to master data, master laws, and apply them. So what exactly is this technology? how to learn it? let's take a look at the three components of data analysis.

Data collection: data collection is our data source. Only when we have enough and reliable data in our hands can we have the basis for data analysis. Data collection can be done through web crawlers and through open source data acquisition.

Data mining: data mining is not only the core part of data analysis, but also where the commercial value lies. By analyzing the data in our hands, we can obtain the law of the relationship between people and things, so as to guide our business activities and achieve a certain commercial value.

Data visualization: through data visualization, we can more intuitively observe the composition and rules of the data, and also better display our analysis results.

As can be seen from the three parts of the above data analysis, the work of a good data analyst includes:

 data collection: open source data usage, web crawler, data integration.

 data mining: data processing, algorithm analysis, data prediction.

 data visualization: data analysis results are presented.

You just need to break down these three aspects one by one, and you can do the job of a data analyst.

1. Break data acquisition

For data collection, we can use some open source data on the network, but this limitation is that you can only use what others open source. If I want to analyze Arena of Valor's hero, if there is no open source data, I will do it myself and have plenty of food and clothing at this time. We can crawl the data on the relevant websites, so the Python crawler is a good tool.

I will take you step by step to complete the web crawler from zero to one, so as to achieve data analysis, no longer too dependent on open source data.

two。 Break data mining

In fact, data mining is the core of data analysis. Only when we successfully dig out the hidden meaning in the data, can the value of our data analysis be reflected. How to mine? at this time, the data algorithm is about to make its debut.

I will take you to learn a variety of data mining algorithms, from the simplest KNN classification algorithm to EM clustering algorithm, from algorithm principles to algorithm combat, step by step to complete data mining.

3. Break data visualization

Data visualization is a good way for us to analyze data and show the results of analysis. Intuitive charts are easier to accept than boring numbers.

I will take you to complete the production of a number of visual charts, so that you can experience the beauty and amazement of numbers.

What can you get from the column?

Through the two modules of "Foundation" and "algorithm", this column tells you the basic knowledge needed for data analysis and the ideas and processes in data analysis, as well as the principles and applications of various algorithms.

I believe that after you have read through the above two modules, you will refresh your understanding of some knowledge. And then through the examples of the column, calmly deal with the technical problems that may be encountered in the future work.

The brief introduction of each module is as follows:

Basic part

This chapter mainly introduces the basic syntax of Python and two common libraries for data analysis, NumPy and Pandas. Coupled with the actual combat of data cleaning and Python crawler, you can further deepen your understanding and get started faster.

At the same time, it will also introduce 10 kinds of Python data visualization charts, and use Matplotlib, Seaborn and pyecherts to make different visual views, so that you can fully understand the similarities and differences between different tools.

Python, as the most popular language, its performance in the field of data analysis is also very amazing. Python has a large number of third-party libraries, which can easily read and write text and obtain data. At the same time, NumPy and Pandas are first-class data processing tools in the industry, which provide great convenience for our data processing. At the same time, Python also has a wealth of visualization modules, Matplotlib, Seaborn and Pyecharts are all outstanding among them, and our visualization work gets twice the result with half the effort. Python also has many machine learning algorithm libraries, such as scikit-learn,jieba, which are very excellent and commonly used modules.

The above knowledge points, I will come one by one in the following chapters, diligent you, will not miss.

I believe that after learning the content of this article, you will be an engineer who has mastered the basic knowledge of Python and can crawl the resources on the network actively and complete the initial data collection according to his own requirements for data. at the same time, you will also be able to skillfully use NumPy and Pandas to process and clean data. And through a variety of visualization operations of the data, the preliminary analysis of the data can be completed.

Algorithm chapter

Algorithm is the soul of data mining, and data mining is the core of data analysis, so learning algorithms well and being able to use them flexibly is a necessary skill for every data analyst.

You must have heard the story of beer and diapers, but have you ever wondered why beer and diapers stab into each other's sales?

There are many emotion analysis systems on the market now. Have you considered the principle behind them?

When you browse a shopping website, why does the website always accurately display the items you care about, and what is the core of it?

If you are really interested in the above content, or want to understand the principle of it, then you might as well complete the content of the algorithm with me.

In this chapter, I will introduce six common algorithms for data analysis, including:

Classification algorithms: KNN, decision tree, SVM and naive Bayes

Clustering algorithms: K-Means and EM

For each algorithm, I will use one section to explain the principle of the algorithm, and then consolidate my knowledge through one or two practical examples in the next section.

It will let you know how to classify items, and if you can make a good prediction. Data analysis is not just the display of data, exploring the value behind the data is the essence and significance of data analysis.

I believe that after learning this article, you will be able to easily classify the heroes in Arena of Valor and choose the one that best suits you. You can also finish the division of the football team and see what level of team you have in mind. Of course, there are many practical examples such as image segmentation, breast cancer detection, emotional analysis and so on, which will take you to complete the perfect transformation from theory to application.

What basis do you need to complete the above?

It's all on the basis of zero. As long as you follow my rhythm, down-to-earth to complete the basic exercises. Even if you don't have any basic Python, as long as you read through the basics of Python, NumPy and Pandas, supplemented by simple exercises, you will certainly be able to complete the rest of the study.

As for algorithms, I also don't need much knowledge of mathematics. I will show you a different world of algorithms in an easy-to-understand language.

Summary

Data analysis to explore the value in the data. Due to the limited space, can not cover all the data analysis knowledge points, please forgive me.

But I hope that through the study of this column, you can quickly accumulate experience and lay a good foundation for you to enter the world of data analysis.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.