In Nushell, a shell designed for working with data, you can perform grouped statistics using a combination of commands that allow you to manipulate and analyze your data efficiently. Here's a step-by-step guide on how to achieve this:

Grouping Data: To group data in Nushell, you can use the group-by command, which is similar to the SQL GROUP BY clause. This command groups rows that have the same values in specified columns. For example, if you have a CSV file and you want to group the data by a specific column, you can use the group-by command with the -k flag to specify the key column:
```
gb.exe -f movies-2.csv -k 3
```
This command will group the data in movies-2.csv by the third column.1
Aggregating Data: Once the data is grouped, you might want to perform aggregations like sum, count, average, etc., on the grouped data. Nushell allows you to extend the group-by command to include aggregations. You can use the --to-table flag to get a table with "groups" and "items" columns, which can then be further processed:
```
--to-table, -:
```
This flag will return a table that can be used for further aggregations.2
Counting Items: If you want to count the number of items in each group, similar to a functional language's countBy function, you can use a pipeline of commands in Nushell. For example, to count the occurrences of each group after grouping:
```
cat test.csv | from csv | group-by name_of_column | length
```
This will give you the count of each group created by the group-by command.4
Summing Values: To sum values of a specific column within each group, you can use the sum command after grouping. For example, if you want to sum the geo_count column after grouping by year:
```
bench -n 10 --pretty { open data.csv | group-by year | sum geo_count }
```
This command will measure the performance of the pipeline and sum the geo_count for each year group.7
Using Nushell's Ecosystem: Nushell has a rich ecosystem of tools and plugins that can be used for data manipulation. You can explore the awesome-nu list for additional tools that might help with grouped statistics:
```
A curated list of awesome tools that work within the nu language ecosystem.
```
This list includes scripts, plugins, and other resources that can be used to extend Nushell's capabilities.3
Installation and Usage: To start using Nushell, you need to install it first. You can install Nushell using Winget, a package management tool for Windows:
```
$ winget install nushell
```
After installation, you can explore Nushell's features and commands to work with your data effectively.5 6
Data Manipulation: Nushell provides elegant and composable commands for working with sequences, records, and tables. This includes grouping and aggregating data, as well as other data manipulation tasks:
```
Anything you can expect to do with sequences, records and tables is doable in Nushell.
```
This flexibility allows you to perform complex data manipulations with ease.8
Understanding Data Structure: Nushell also allows you to understand and manipulate the structure of your data. For example, if you have a record and you want to get a list of keys, you can use the appropriate command to extract them:
```
I have a record {a:1, b:2}. I would like to know how to get list of keys from it, which would return [a b] in this case.
```
This understanding of data architecture helps in performing grouped statistics accurately.10

By combining these commands and techniques, you can perform grouped statistics in Nushell to analyze and summarize your data effectively.