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In this issue, Xiaobian will bring you about what data types are in pandas. The article is rich in content and analyzed and described from a professional perspective. After reading this article, I hope you can gain something.

What do pandas do? Python Data Analysis Library or pandas is a NumPy based tool created to solve data analysis tasks. Pandas incorporates a large number of libraries and standard data models, providing the tools needed to efficiently manipulate large data sets. Pandas provides a number of functions and methods that allow us to process data quickly and easily. As you'll soon discover, it's one of the important factors that makes Python a powerful and efficient data analytics environment. Simple summary is a tool for processing large data. The data processing software commonly used in our lives is Microsoft Excel. When you learn pandas, you will find that pandas are much better than Excel.

How do you do it or how do you process the data?

Simply speaking, pandas only have two data types, Series and DataFrame. Series can be simply understood as rows or columns in Excel. DataFrame can be understood as the entire Excel table. Of course, this is only an image understanding. In fact, their functions are more flexible than Excel.

Series: One-dimensional array, similar to the one-dimensional array in Numpy. They are also very similar to Python's basic data structure List. Series can now store different data types, strings, boolean values, numbers, etc. can be stored in Series.

Time- Series: Series indexed by time.

DataFrame: Two-dimensional tabular data structure. Many functions are similar to data.frame in R. A DataFrame can be understood as a container for a Series. The following content is mainly based on DataFrame.

Panel: A three-dimensional array that can be understood as a container for DataFrame.

The above is what data types are in the pandas shared by Xiaobian. If there are similar doubts, please refer to the above analysis for understanding. If you want to know more about it, please pay attention to the industry information channel.

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