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This article mainly explains "how to use Python to batch process meteorological data sets with daily resolution". The explanation in this article is simple and clear, easy to learn and understand. Please follow the ideas of Xiaobian to study and learn "how to use Python to batch process meteorological data sets with daily resolution".

Do you like data sets stored in TXT text? Meteorological data is often used in research a class of data sets, its storage is actually more standardized, generally see is TXT text format, but this does not seem to be very convenient when we specifically use, we hope the data is stored in Excel spreadsheet, and can filter their needs of the site, time or matching variables. So, let's look at what this TXT data looks like. It's a multi-element meteorological dataset with a time length of 1960 - 2018, and a time resolution of every day, and a folder with TXT data stored under it every year.

No mistake, these data are all in text format, not the Excel data I want, because I think Excel storage is more convenient to query and extract, so it can save a lot of time, then I will process all these data into annual classification, every year is an Excel spreadsheet, which stores all the sites, so the result is 59 years of data, that is, 59 spreadsheets, why to store separately In fact, there are reasons, Because I am worried that a spreadsheet in Excel is not enough to store these data, it seems that a spreadsheet can only store 1.04 million rows of data. If I remember correctly, haha, I remember correctly. The key code is given below:

Next up are the results of processing, 59 data sets stored separately by year:

If you dislike these Excel is scattered, don't worry, there are ways to solve, by opening Excel macro through VB code can be very convenient to merge a large number, but this may lead to data loss, because the data is relatively large, Excel storage is not so much

Thank you for reading, the above is the content of "how to use Python to batch process meteorological data sets with daily resolution". After studying this article, I believe everyone has a deeper understanding of how to use Python to batch process meteorological data sets with daily resolution. The specific use situation still needs to be verified by practice. Here is, Xiaobian will push more articles related to knowledge points for everyone, welcome to pay attention!

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