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NumPy group function, with a example and step by step guide, python in windows 11 or windows 10 or ubuntu or fedora

 NumPy is a Python library that is widely used for scientific computing, especially in the field of data analysis. One of the key features of NumPy is the ability to perform grouping operations on arrays using the `groupby()` function. 

Here's an example of how to use the `groupby()` function in NumPy: 

Suppose you have an array of sales data for different stores over the course of a week: 




This array contains three columns: the store ID, the day of the week, and the sales for that day. You can use the `groupby()` function to group the sales data by store ID: 


In this example, we split the sales data array into subarrays based on the unique store IDs in the first column. Then, for each subarray, we calculate the total sales by summing the values in the third column. Finally, we print out the total sales for each store. The output of this code would be: 


This is just one example of how to use the `groupby()` function in NumPy. It can be used for many different types of grouping operations on arrays, and is a powerful tool for data analysis and manipulation. 

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