duckdb <<'SQL'
SELECT column1, COUNT(*) AS cnt
FROM 'data.csv'
GROUP BY column1
ORDER BY cnt DESC;
SQL

Load All Data

SELECT * FROM 'data.csv';

Select Specific Columns

SELECT column1, column2, column3
FROM 'data.csv';

Filter Rows

Retrieve only rows matching a specific condition:

SELECT *
FROM 'data.csv'
WHERE column1 = 'value';

Filter with multiple conditions:

SELECT *
FROM 'data.csv'
WHERE column1 = 'value'
  AND column2 > 100;

Combined Column and Row Filtering

SELECT column1, column2
FROM 'data.csv'
WHERE column1 LIKE '%keyword%'
  AND column3 IS NOT NULL;

Sorting

SELECT *
FROM 'data.csv'
ORDER BY column1 ASC, column2 DESC;

Aggregation

-- Count, sum, average
SELECT
  column1,
  COUNT(*) AS cnt,
  SUM(column2) AS total,
  AVG(column2) AS avg_val,
  MIN(column2) AS min_val,
  MAX(column2) AS max_val
FROM 'data.csv'
GROUP BY column1
HAVING COUNT(*) > 5
ORDER BY cnt DESC;

Distinct Values

SELECT DISTINCT column1
FROM 'data.csv'
ORDER BY column1;

Join Multiple CSVs

SELECT a.id, a.name, b.amount
FROM 'users.csv' AS a
JOIN 'orders.csv' AS b ON a.id = b.user_id;

Filter by Row Number

Retrieve a specific range of rows (e.g., rows 11-20):

SELECT *
FROM (
    SELECT *, row_number() OVER () AS rn
    FROM 'data.csv'
)
WHERE rn BETWEEN 11 AND 20;

Additional SQL Features

Refer to the official documentation only when you need other features.

Reference Documentation:

csv-analysis

CSV Analysis with DuckDB

Execution

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