agg

Create a GIF

$ agg [path/to/demo.cast] [path/to/demo.gif]

agg [OPTIONS] [FILE...]
or
command | agg [OPTIONS]

-g FIELD...
    Specifies one or more fields to group data by. Records with identical values in these fields will be grouped together for aggregation.

-s FIELD
    Calculates the sum of numerical values in the specified field for each group.

-a FIELD
    Computes the average of numerical values in the specified field for each group.

-c FIELD
    Counts the number of records within each group, optionally based on a specific field.

-m FIELD
    Finds the minimum numerical value in the specified field for each group.

-M FIELD
    Finds the maximum numerical value in the specified field for each group.

-o FIELD...
    Specifies the output order and inclusion of grouped fields and aggregated results.

-d DELIMITER
    Sets the input and/or output field delimiter (e.g., ',' for CSV, '\t' for TSV). Defaults to whitespace.

-H
    Treats the first line of input as a header row, which is then processed separately or used for field naming in output.

The agg command is not a standard, widely distributed utility found in most common Linux distributions. This analysis describes a conceptual command that would typically perform data aggregation tasks on structured text data, similar to the functionality provided by SQL's GROUP BY clause. If it existed, agg would likely be designed to process input (from files or standard input) and compute summary statistics based on specified grouping criteria. For example, it could sum numerical values, calculate averages, count occurrences, find minimums or maximums, or concatenate strings within groups of records that share common key values. This type of command would be invaluable for tasks such as generating reports, summarizing log files, analyzing datasets, and performing basic business intelligence directly from the command line. Its primary goal would be to transform detailed input data into a more concise, aggregated output, facilitating quicker insights and further analysis without requiring complex scripts or dedicated database systems. Users seeking such functionality typically rely on a combination of existing powerful text processing tools or specialized utilities designed for data manipulation.

The agg command is not a standard, universally available utility in common Linux distributions. This analysis describes a conceptual command that would perform data aggregation, based on the common meaning of 'agg' (aggregate). Users typically achieve similar functionality using combinations of standard tools like awk, sort, uniq, cut, datamash, or scripting languages like Python/Perl. Therefore, attempting to execute 'agg' on a typical Linux system will likely result in a 'command not found' error.

Since a standard agg command is not available, users can achieve similar data aggregation results using a combination of powerful existing Linux utilities or specialized tools:

Command Line Tools: For simple aggregations, tools like sort and uniq -c can count unique occurrences. For more complex numerical calculations (sums, averages), awk is highly versatile, allowing users to group data and perform calculations. The datamash utility is a dedicated tool specifically designed for various forms of numerical and textual data aggregation on tabular data.

Scripting Languages: For highly complex aggregation logic, multi-step processes, or integration with other data sources, scripting languages such as Python or Perl are often employed. They offer robust data structures (like dictionaries/hashes) that are ideal for grouping and aggregating data programmatically.

Understanding the capabilities of these tools allows users to build powerful data processing pipelines on the Linux command line, effectively replacing the need for a dedicated 'agg' command.

As agg is not a standard Linux command, it does not have a documented history of development or widespread usage in official repositories. The concept of 'aggregation' itself is fundamental to data processing and has been implemented in various forms across many tools and programming languages. While a dedicated 'agg' command might exist in specific, niche environments or as a custom script, it lacks a common lineage or evolutionary path within the broader Linux ecosystem.

awk(1), sort(1), uniq(1), cut(1), datamash(1)