Basic understanding of Python processing data, what Python uses to process databases

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1. How to use python language for data analysis?

With the continuous development of the Internet, data analysis has become one of the main basis to guide our work direction, and Suisan today we will take a look together, such as how to use python programming development for data analysis, the following computer training will start Today's main content.

Why learn Python for data analysis?

Python has recently attracted a lot of interest as a language for data analysis. I have learned the basics of Python before. Here are some reasons in favor of learning Python:

Open source - free to install

Awesome online community

easy to learn

Can become the lingua franca of data science and web-based analytics product generation

Needless to say, it also has some disadvantages:

It's an interpreted language rather than a compiled language - so may use more CPU time. However, it's still a good choice considering it saves programmer's time (due to ease of learning).

Python2.7 and 3.4

This is one of the controversial topics in Python. You will definitely come across it, especially if you are a beginner. There is no right/wrong choice here. It all depends on the situation and your needs. I will try to give you some advice to help you make an informed choice.

Why Python2.7?

Great community support! This is what you need in your early years. Python2 was released in late 2000 and has been in use for over 15 years.

Too many third-party libraries! While many libraries provide 3.x support, there are still many modules that only work on 2.x versions. If you plan to use Python for a specific application, such as web development that relies heavily on external modules, you may be better off with 2.7.

2. How does python process image data?

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Generate a solid color image

First set the color of the picture, and then use the new method of the Image module to generate a new picture. The picture in png format needs to be set to rgba, similar to rgb, L (grayscale, etc.), and the size is set to 640. 480, this can be set according to your own situation, the same is true for the color.

Generate pictures in batches

One picture is generated above, so how about generating ten pictures, the steps are the same, but the color is changed, and the loop can be used to solve it. First create a color list and put the color of the picture to be generated into it. Then cycle to obtain different colors, and use the string splicing method to change the name of the picture when saving.

locally generated images

packaged as a function

The previous method can already generate images in batches. For greater versatility, we can encapsulate them into functions and separate out the parameters that can be changed. The same is true for the size. When using it, you can define the color list and size according to your own needs. Of course, there are some prompts and error reporting compatibility, so I won’t talk about it here.

The picture beam draft generated by this slag slippery ground

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Origin blog.csdn.net/chatgpt001/article/details/131921257