Command Line Data Analysis

Analyze CSV, JSON, and text data entirely from your terminal — no Excel, no pandas, no Jupyter.

Published: June 1, 2026 · Tools: evolver-tools (262 CLI tools) · Reading time: 10 min

Why the Terminal?

Spreadsheets are great for small, visual data. Jupyter is great for complex pipelines. But for quick analysis — getting stats, filtering rows, transforming formats — the command line is faster. One command, instant output, pipe it into the next tool.

This guide uses evolver-tools, a collection of 262 zero-dependency CLI tools. Everything runs on pure Python — no npm install, no apt-get, no compiling.

Try it right now

Install all 262 tools in 3 seconds:

pip install evolver-tools
View on GitHub →

Part 1: CSV Data Analysis

CSV is the lingua franca of data. Logs, exports, reports — they all come as CSV. Here's how to analyze them without opening Excel or Google Sheets.

Get an Overview: `evtool csv-stats`

The first thing you want with any CSV is a quick overview — column names, types, row count, nulls, min/max values.

$ evtool csv-stats sales.csv
File: sales.csv — 10,000 rows × 8 columns

Column              Type      Non-Null    Min         Max         Mean
──────────────────────────────────────────────────────────────────────
date                date      10,000      2024-01-01  2024-12-31  —
product             string    10,000      —           —           —
category            string    9,876       —           —           —
quantity            int       10,000      1           500         23.4
unit_price          float     10,000      4.99        2,499.00    89.50
total               float     10,000      4.99        24,990.00   1,245.30
region              string    10,000      —           —           —
sales_rep           string    8,234       —           —           —

⚠ 124 missing values in category
⚠ 1,766 missing values in sales_rep

Running evtool csv-stats --all data.csv gives you mode, stddev, percentiles, and histogram in one shot.

Filter Rows: `evtool csv-filter`

Find rows matching a condition — like all transactions over $1,000 in Q3:

$ evtool csv-filter --query 'total > 1000 and region == "West"' sales.csv
date,product,category,quantity,unit_price,total,region,sales_rep
2024-07-15,MacBook Pro,Electronics,2,2,499.00,4,998.00,West,Alice C.
2024-08-03,Surface Pro,Electronics,1,1,899.00,1,899.00,West,Bob K.
2024-09-21,Server Rack,Hardware,1,12,000.00,12,000.00,West,Alice C.
... (1,234 rows total)

Select & Project Columns: `evtool csv-select`

$ evtool csv-select --columns product,region,total sales.csv | head -5
product,region,total
MacBook Air,East,1,199.00
ThinkPad X1,West,2,499.00
Dell Monitor,South,349.00
iPad Pro,East,999.00

Group & Aggregate: `evtool csv-stats --group-by`

$ evtool csv-stats --group-by category sales.csv
Category        Count    Total(mean)  Total(sum)
─────────────────────────────────────────────
Electronics     3,421    $1,892.30    $6,473,932
Hardware        2,108    $4,231.50    $8,919,145
Software        2,876    $345.20      $993,355
Accessories     1,595    $89.50       $142,813

Sort Data: `evtool csv-sort`

$ evtool csv-sort --by total --desc sales.csv | head -5
date,product,category,quantity,unit_price,total,region,sales_rep
2024-06-15,Enterprise Server,Hardware,5,24,990.00,124,950.00,Central,David M.
2024-11-02,Mac Pro Bundle,Electronics,3,18,500.00,55,500.00,East,Alice C.
2024-03-18,Data Center Rack,Hardware,2,24,000.00,48,000.00,West,Frank L.

Convert CSV to JSON: `evtool csv-to-json`

$ evtool csv-to-json sales.csv | head -20
[
  { "date": "2024-01-03", "product": "MacBook Air", "category": "Electronics",
    "quantity": 2, "unit_price": 1199.0, "total": 2398.0, "region": "East", "sales_rep": "Alice C." },
  { "date": "2024-01-07", "product": "ThinkPad X1", "category": "Electronics",
    "quantity": 1, "unit_price": 2499.0, "total": 2499.0, "region": "West", "sales_rep": "Bob K." }
]

Join Two CSVs: `evtool csv-join`

$ evtool csv-join --left sales.csv --right products.csv --on product_id
date,product,category,total,product_id,name,stock
2024-01-03,MacBook Air,Electronics,2398.00,p1001,MacBook Air M3,45
2024-01-07,ThinkPad X1,Electronics,2499.00,p1002,ThinkPad X1 Gen 12,12

Real-World Pipeline: Weekly Sales Report

Combine everything into a shell pipeline:

$ evtool csv-filter --query 'date >= "2024-12-01"' sales.csv \
  | evtool csv-select --columns category,total,region \
  | evtool csv-stats --group-by category
Category      Count    Total(mean)  Total(sum)
───────────────────────────────────────────
Electronics   412      $1,445.00    $595,340
Hardware      298      $3,890.00    $1,159,220
Software      356      $312.00      $111,072
Accessories   210      $78.00       $16,380

Part 2: JSON Data Processing

APIs return JSON. Logs are JSON. Configs are JSON. Here's how to explore and transform JSON from the terminal.

Pretty-Print JSON: `evtool json-pretty`

$ evtool json-pretty response.json
{
  "status": "ok",
  "data": {
    "users": [
      {
        "id": 1,
        "name": "Alice",
        "email": "alice@example.com",
        "role": "admin",
        "last_login": "2024-12-15"
      },
      ...
    ],
    "total": 234
  }
}

Validate & Find Issues: `evtool json-validate`

$ evtool json-validate config.json
✓ Valid JSON

$ evtool json-validate broken.json
✘ Parse error at line 42, column 15:
   Unexpected token '}' — expected property name

Select Fields from JSON: `evtool json-select`

$ cat response.json | evtool json-select --key data.users[].name
["Alice", "Bob", "Charlie", "Diana"]

Convert JSON to CSV: `evtool json-to-csv`

$ evtool json-to-csv users.json | head -3
id,name,email,role,last_login
1,Alice,alice@example.com,admin,2024-12-15
2,Bob,bob@example.com,user,2024-12-10

Merge Multiple JSON Files: `evtool json-merge`

$ evtool json-merge --deep config.default.json config.prod.json
{
  "host": "api.example.com",
  "port": 443,
  "debug": false,
  "database": {
    "url": "postgres://prod:****@db.internal:5432/app",
    "pool_size": 20
  }
}

Part 3: Text & System Data

Text Statistics: `evtool text-stats`

$ evtool text-stats README.md
Lines:        1,247
Words:        8,432
Characters:   52,198
Avg line len: 41.8 chars
Longest line: 187 chars (line 892)
Empty lines:  124

Quick System Health: `evtool sys-info`

$ evtool sys-info
Host:     myserver
OS:       Linux 6.2.0 (x86_64)
CPU:      8 cores @ 3.4 GHz — Load: 1.2 / 8.0
Memory:   15.6 GB / 31.2 GB (50%)
Disk:     234 GB / 512 GB (46%)
Uptime:   14d 3h 22m
Python:   3.11.5

Disk Usage Snapshot: `evtool disk-usage`

$ evtool disk-usage /var/log
Directory                    Size      Files
─────────────────────────────────────────────
/var/log/nginx               1.2 GB    89
/var/log/journal             890 MB    47
/var/log/syslog              234 MB    12
/var/log/mysql               178 MB    34
/var/log/auth.log            45 MB     1

Countdown Timer: `evtool countdown`

$ evtool countdown 5m "Build complete!"
⏳ 4:59 ... 4:58 ... 4:57 ...
⏰ Build complete!

Part 4: Piping Everything Together

The real power is composition. Pipe data between tools just like Unix utilities:

Pipeline	What it does
`evtool csv-to-json data.csv \| evtool json-pretty`	CSV → formatted JSON
`evtool json-to-csv api.json \| evtool csv-stats --all`	API response → stats
`evtool csv-filter --query 'price > 50' \| evtool csv-sort --by price`	Filter + sort in one pipeline
`find logs/ -name '*.json' \| evtool json-validate --batch`	Validate all JSON files at once
`curl -s api.example.com/stats \| evtool json-select --key data`	Quick API data extraction

Why evolver-tools?

There are many CLI tools for data processing — jq, yq, xsv, milller, visidata. Each installs separately, with different syntax and runtime dependencies.

evolver-tools is different:

Zero dependencies — pure Python stdlib. No npm, no cargo, no brew.
262 tools, one install — pip install evolver-tools gives you everything.
Cross-platform — Linux, macOS, WSL, even Windows with Python.
Pipe-friendly — standard Unix I/O, works in any pipeline.
CI-ready — installs in 3 seconds, no network after cache.

Ready to try it?

Install in 3 seconds. No dependencies. Works everywhere.

pip install evolver-tools
⭐ Star on GitHub

What's Next?

Browse all 262 tools: evolver-tools catalog
Printable quick reference: Cheatsheet
Real-world CSV walkthrough: CSV CLI Tutorial
Price & plans: Pricing
The story behind this project: Built by AI

Command Line Data Analysis

Why the Terminal?

Try it right now

Part 1: CSV Data Analysis

Get an Overview: evtool csv-stats

Filter Rows: evtool csv-filter

Select & Project Columns: evtool csv-select

Group & Aggregate: evtool csv-stats --group-by

Sort Data: evtool csv-sort

Convert CSV to JSON: evtool csv-to-json

Join Two CSVs: evtool csv-join

Real-World Pipeline: Weekly Sales Report

Part 2: JSON Data Processing

Pretty-Print JSON: evtool json-pretty

Validate & Find Issues: evtool json-validate

Select Fields from JSON: evtool json-select

Convert JSON to CSV: evtool json-to-csv

Merge Multiple JSON Files: evtool json-merge

Part 3: Text & System Data

Text Statistics: evtool text-stats

Quick System Health: evtool sys-info

Disk Usage Snapshot: evtool disk-usage

Countdown Timer: evtool countdown

Part 4: Piping Everything Together

Why evolver-tools?

Ready to try it?

What's Next?

Get an Overview: `evtool csv-stats`

Filter Rows: `evtool csv-filter`

Select & Project Columns: `evtool csv-select`

Group & Aggregate: `evtool csv-stats --group-by`

Sort Data: `evtool csv-sort`

Convert CSV to JSON: `evtool csv-to-json`

Join Two CSVs: `evtool csv-join`

Pretty-Print JSON: `evtool json-pretty`

Validate & Find Issues: `evtool json-validate`

Select Fields from JSON: `evtool json-select`

Convert JSON to CSV: `evtool json-to-csv`

Merge Multiple JSON Files: `evtool json-merge`

Text Statistics: `evtool text-stats`

Quick System Health: `evtool sys-info`

Disk Usage Snapshot: `evtool disk-usage`

Countdown Timer: `evtool countdown`