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This article will explain in detail how to analyze the pivot_table PivotTable. The content of the article is of high quality, so the editor will share it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

PivotTable is a powerful tool for classifying and summarizing data and statistical analysis. By setting new row label index and column label columns, specifying the numerical values to be statistically analyzed, specifying the statistical aggregation function aggfunc, etc., PivotTable can be used to analyze the original data table from multiple perspectives and reshape it in different ways, so it is called PivotTable.

In the Pandas of Python, you can use the groupby method or pivot_table function to complete the classification and summary to achieve the function of PivotTable. Groupby is first grouped, and then the aggregate function is selected to generate a PivotTable. Pivot_table generates PivotTable directly by setting parameters such as index,columns,values,aggfunc.

First, PivotTable in Excel

The PivotTable in Excel can set rows (index), columns (columns), values (values), and select aggregate functions through value field settings. The graphical interface is relatively simple to operate, but not flexible and powerful enough.

Second, pivot_table PivotTable

Compared with the PivotTable in Excel, using the pivot_table function of pandas to implement the PivotTable will be very flexible and powerful.

Construct dataframe data

1the parameter of index

2Parameters of columns

3Parameters of values

4the parameter of dint aggfunc

5 Overview of the parameters of the initialtable

Third, groupby data packet function

Using the grouping function of groupby method combined with aggregate function can also achieve PivotTable effect, which is also a very common method in data analysis. The demonstration operation is as follows.

On how to analyze the pivot_table PivotTable to share here, I hope that the above content can be of some help to you, can learn more knowledge. If you think the article is good, you can share it for more people to see.

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