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miller (mlr) is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON. Stream processing for structured data with powerful transformation capabilities.

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Basic Usage

• mlr --csv cat file.csv - Read CSV

• mlr --tsv cat file.tsv - Read TSV

• mlr --json cat file.json - Read JSON

• mlr --csv head -n 10 file.csv - First 10 rows

• mlr --csv tail -n 10 file.csv - Last 10 rows

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Field Selection

• mlr --csv cut -f field1,field2 file.csv - Select fields

• mlr --csv cut -x -f field1 file.csv - Exclude field

• mlr --csv cut -o -f field1 file.csv - Only field

• mlr --csv rename field1,newfield1 file.csv - Rename field

• mlr --csv rename -r 'old(.*)', 'new$1' file.csv - Rename with regex

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Filtering

• mlr --csv filter '$field == "value"' file.csv - Equal filter

• mlr --csv filter '$field > 10' file.csv - Numeric filter

• mlr --csv filter '$field =~ "pattern"' file.csv - Regex filter

• mlr --csv filter '$field != "value"' file.csv - Not equal

• mlr --csv filter '$field1 == "a" && $field2 > 5' file.csv - Multiple conditions

• mlr --csv filter -x '$field == "value"' file.csv - Exclude matching

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Transformation

• mlr --csv put '$new = $old * 2' file.csv - Add computed field

• mlr --csv put '$total = $price * $quantity' file.csv - Calculate

• mlr --csv put '$date = strftime($timestamp, "%Y-%m-%d")' file.csv - Format date

• mlr --csv put '$upper = toupper($field)' file.csv - String functions

• mlr --csv put '$len = length($field)' file.csv - String length

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Sorting

• mlr --csv sort -f field1 file.csv - Sort by field

• mlr --csv sort -f field1,field2 file.csv - Sort by multiple fields

• mlr --csv sort -nr -f field1 file.csv - Reverse numeric sort

• mlr --csv sort -f field1 -t field2 file.csv - Sort then tie-break

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Grouping & Aggregation

• mlr --csv stats1 -a count -f field1 -g category file.csv - Count by group

• mlr --csv stats1 -a sum -f amount -g category file.csv - Sum by group

• mlr --csv stats1 -a mean -f value -g category file.csv - Mean by group

• mlr --csv stats1 -a min,max -f value -g category file.csv - Min/max

• mlr --csv group-by category file.csv - Group records

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Joining

• mlr --csv join -j field1 -f file1.csv file2.csv - Inner join

• mlr --csv join -j field1 -l file1.csv file2.csv - Left join

• mlr --csv join -j field1 -r file1.csv file2.csv - Right join

• mlr --csv join -j field1 -u file1.csv file2.csv - Full outer join

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Format Conversion

• mlr --csv --json cat file.csv - CSV to JSON

• mlr --json --csv cat file.json - JSON to CSV

• mlr --csv --tsv cat file.csv - CSV to TSV

• mlr --csv --markdown cat file.csv - CSV to Markdown

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Common Examples

Select Fields

mlr --csv cut -f name,email users.csv

Extract specific columns.

Filter Rows

mlr --csv filter '$status == "active"' users.csv

Filter by condition.

Add Field

mlr --csv put '$total = $price * $qty' orders.csv

Calculate new field.

Sort

mlr --csv sort -f date -nr sales.csv

Sort by date descending.

Group Statistics

mlr --csv stats1 -a sum -f amount -g category sales.csv

Sum by category.

Join Files

mlr --csv join -j user_id -f users.csv orders.csv

Join on common field.

Convert Format

mlr --csv --json cat data.csv > data.json

Convert CSV to JSON.

Multiple Operations

mlr --csv filter '$age > 18' then cut -f name,email then sort -f name users.csv

Chain operations with 'then'.

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Tips

• Use --csv, --tsv, --json to specify input format

• Chain operations with 'then' keyword

• Use $field to reference fields in expressions

• Supports streaming for large files

• Great for data transformation pipelines

• More intuitive than awk for structured data

• Supports many statistical functions

• Excellent documentation and examples