Chat with Excel & CSV — plain English to results.

Generated operation & example result

// In-memory aggregation result
GROUP BY category
SUM(revenue) AS total_revenue
ORDER BY total_revenue DESC

// Example results:
// Electronics:  $124,500
// Clothing:     $87,200
// Home & Garden: $53,100

Groups all rows by the category column, sums the revenue column for each group, and orders by total descending.

Generated operation & example result

// In-memory filter result
FILTER WHERE
  order_date >= first_day_of_current_month
  AND total_amount > 500

// Returns matching rows from the spreadsheet
// with all columns preserved.

Filters rows based on date and amount conditions — equivalent to a complex FILTER formula in Excel.

Generated operation & example result

// Cross-sheet join result
JOIN Orders ON Orders.CustomerID = Customers.CustomerID

// Returns merged rows with columns from both sheets:
// CustomerID, CustomerName, Email, OrderDate,
// OrderTotal, ProductName, Quantity

Performs an in-memory join across two sheets — replaces nested VLOOKUP or INDEX/MATCH formulas.

Generated operation & example result

// In-memory aggregation result
GROUP BY MONTH(order_date), YEAR(order_date)
WHERE YEAR(order_date) = 2024
AVG(order_total) AS avg_order_value
ORDER BY month ASC

// Example results:
// January 2024: $127.50
// February 2024: $134.20
// March 2024: $142.80

Groups by month and year, calculates average order value for each period, and orders chronologically.

Generated operation & example result

// In-memory count result
COUNT(*) WHERE status = 'Approved'

// Returns: 847 rows match the filter.

Simple count with a filter condition — equivalent to COUNTIF in Excel.

Generated operation & example result

// In-memory duplicate detection
GROUP BY email
HAVING COUNT(*) > 1
SELECT email, COUNT(*) AS occurrences

// Example results:
// john@example.com — 3 times
// jane@example.com — 2 times

Groups by email and filters for groups with more than one occurrence — reveals duplicates without manual formula work.

Generated operation & example result

// In-memory aggregation result
GROUP BY product_name
SUM(quantity) AS total_quantity
ORDER BY total_quantity DESC
LIMIT 10

// Example results:
// Widget A:  1,240 units
// Widget B:  987 units
// Widget C:  854 units

Groups by product, sums quantity across all rows, sorts descending, and returns the top 10.

Generated operation & example result

// In-memory aggregation result
GROUP BY department
SUM(amount) AS total_expenses
ORDER BY total_expenses DESC

// Example results:
// Engineering: $342,100
// Marketing:   $128,500
// Operations:  $94,200

Aggregates expense amounts by department — replaces a pivot table with a plain-English question.