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This article mainly introduces "how to build a professional Python big data analysis environment". In daily operation, I believe many people have doubts about how to build a professional Python big data analysis environment. The editor consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful to answer the doubts about "how to build a professional Python big data analysis environment". Next, please follow the editor to study!

01 what is data science

Data science is often described as the intersection of statistics and programming. In this article, we will show you how to set up a professional data science environment on your computer so that you can start hands-on and popular data science libraries!

What is a professional data science environment? There is a general consensus that it appears for two reasons:

Programming language: Python 3. There are many experienced data scientists who continue to use R-especially if they have a strong statistical background. But overall, Python is a more generic and popular programming language that can more easily solve a wide range of problems, from web fetching and data cleaning to modeling and building dashboards or producing your model. Today, most data scientists use Python 3.

Edit: Jupyter Notebook-- has many great text editors for editing Python code, such as Visual Studio Code, which is a popular free choice. But it's really hard to beat Jupyter Notebook to create shareable files that allow you to easily interlace comments, code, and diagrams.

The easiest way to install Python and Jupyter notebooks is through the free Anaconda distribution. It also includes many of the data science packages you need, such as pandas,statsmodels and scikit-Learn.

The installation process depends on whether you are using Windows or Mac or linux. What we are talking about today is if you install it on a Windows system.

02 installation process

Click the download button on Python 3.

A window pops up asking if you are willing to provide your information to Python-you don't need to do so unless you do.

You should see a .exe file being downloaded at the bottom of the browser window. When the download is complete, click the arrow to the right of the file name in the lower left corner of the browser and select "open".

If you can't see the file in your browser, you can also open Windows Explorer, navigate to the "download" directory, and double-click the Anaconda file in the list to open it.

This will open the Anaconda installer, which will install the software on your computer.

Click Next, and then click I agree to accept the license, and then you can install for Just me and click Next. Then select the destination folder (the default value should apply to most people).

On the next screen, make sure the add anaconda to my path environment check box is selected. It will tell you that this is not recommended, but it is necessary to be able to access Anaconda from the command line, and it will give you maximum flexibility when working on a project. Then click install.

This step may take a few minutes.

Once the installation is complete:

Click "next". You can skip the installation of Microsoft Visual Code Studio or PyCharm.

Finally, click finish.

It opens a browser window that you can close directly.

This is the process of installing Anaconda! The next step is to test your installation

03 test

To test the installation, click start on Windows, and then click Anaconda Navigator in the list of programs (or search for "Anaconda Navigator" in the search bar and select "Anaconda Navigator").

On the Mac computer, open Finder and Anaconda Navigator in the Applications folder.

Anaconda Navigator is one of the ways that you will be able to run Jupyter notebook:

At this point, the study on "how to build a professional Python big data analysis environment" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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