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CSV row filter guide

How to filter CSV rows with nested AND/OR conditions

Open Filter rows

For example, keep orders worth at least USD 1,000 by selecting the amount column, choosing Number, and setting the threshold. Check the source format before running because text and number conditions follow different rules.

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Related tool: Filter rows

Example: orders worth at least USD 1,000

Extract higher-value orders for review. The Amount column must contain valid decimal numbers without currency symbols, thousands separators, or surrounding spaces.

  • Column: Amount USD
  • Value type: Number
  • Condition: Greater than or equal to 1000

CSV before filtering

All values in Amount USD use a numeric format accepted by the tool.

sales.csv
Order ID,State,Amount USD,Owner
S001,California,1280.00,Ava
S002,Oregon,840.00,Noah
S003,Texas,2150.00,Mia
S004,California,990.00,Liam

Rows that meet the threshold

Two of the four input rows match and keep their original order; the other two are excluded.

sales_filtered.csv
Order ID,State,Amount USD,Owner
S001,California,1280.00,Ava
S003,Texas,2150.00,Mia

Filter a CSV in five steps

Use the preview to confirm both the column number and header.

  1. Open Filter rows and select the CSV.
  2. Check encoding, delimiter, headers, and sample values.
  3. Choose the column and Text or Number.
  4. Set the comparison, value, and case option when relevant.
  5. Run it, confirm every input row is either in the result or excluded, and download.
Filter rows

Common filtering mistakes

Values that look similar on screen may still differ in the CSV, and grouping changes the result.

  • Using commas or a dollar sign in numeric cells
  • Expecting an exact match for a value with trailing space
  • Comparing mixed date formats as plain text
  • Grouping an AND/OR branch at the wrong level

When filtering is the right operation

It fits both simple checks and grouped business rules that keep only matching rows.

  • Good fit: status AND region
  • Good fit: alternative numeric thresholds with OR
  • Use deduplication for repeated rows
  • Date-aware logic is outside the current scope