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from $1.40 / 1,000 kept rows

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Dataset Filter & Transform

Try for free

Returns rows of any Apify dataset, CSV/Excel/JSON file URL or Google Sheet that pass filter rules (25 operators, AND/OR, date ranges that fix a scraper's ignored date filter) after transforms (rename, cast, compute, regex), then sort, dedupe, export, webhook. Agent-ready: pay per event (x402, MCP).

Pricing

from $1.40 / 1,000 kept rows

Rating

0.0

(0)

Developer

Adam Pearce

Actor stats

Bookmarked

Total users

Monthly active users

7 days ago

Last modified

Categories

Developer tools

Automation

Agents

Dataset to process

datasetId

Optional

Pick an existing Apify dataset (for example the output of any scraper run). Use this OR 'File URL' OR 'Data (inline)' below. Declaring it this way is what lets this Actor run with limited permissions: it may read the dataset you point at, and nothing else on your account.

Type:string

File URL (CSV, Excel, JSON or JSON Lines)

fileUrl

Optional

Instead of a dataset, download the rows from a public link: a CSV or TSV file, an Excel .xlsx file (first sheet, header row), a JSON array or JSON Lines file, or a Google Sheet (paste the normal sheet link, sharing set to 'Anyone with the link can view'). The format is detected automatically. Up to 100 MB per run. The download is never charged; only rows you keep are.

Type:string

File format

fileFormat

Optional

Only needed if automatic detection gets the file URL's format wrong.

Type:string

Default:auto

Options:

autocsvtsvjsonjsonlxlsx

Data (inline)

data

Optional

A JSON array of records to filter and transform, for ad-hoc data instead of a dataset ID or file URL.

Type:array

Transform steps (applied in order, before filtering)

transforms

Optional

A list of steps applied to every row, top to bottom, before any filtering happens. Each step writes a top-level field. Dotted paths like 'address.city' can be read by copy, addField placeholders, compute, default, coalesce, replace, split, joinArray, substring, round, dateFormat, dateDiff, extractDomain, mapValues, hash, parseJson and length; rename, drop, keep, cast, trim, uppercase, lowercase and regexExtract only work on top-level fields, so copy a nested value to a top-level field first. Steps (26): rename {from,to}; drop {fields}; keep {fields} (drop everything else); copy {from,to}; setField {field,value}; default {field,value} (fill blanks); addField {field,template} ({{a}} {{b.c}} placeholders); compute {field,expression,round} (arithmetic + - * / over numeric fields); cast {field,to: number|string|boolean}; trim / uppercase / lowercase {field}; replace {field,search,replacement,regex,into}; regexExtract {field,pattern,group,into}; split {field,separator,index,into}; joinArray {field,separator}; substring {field,start,length,into}; round {field,decimals}; coalesce {fields,into} (first non-blank); dateFormat {field,format: iso|date|unix|unixMs|'DD/MM/YYYY',into}; dateDiff {from,to (a field or 'now'),unit: days|hours|minutes|seconds,into}; extractDomain {field,into} (from an email or URL); mapValues {field,map,default,into} (look up values in a {from: to} table); hash {fields,algorithm,into} (a stable id for dedupe); parseJson {field}; length {field,into}.

Type:array

Filter conditions (applied after transforms)

filters

Optional

Rows are kept only if they pass these conditions (combined per 'Combine filters with' below). Each item: {"field": "revenue", "operator": "greaterOrEqual", "value": 1000}. Operators: equals, notEquals, contains, notContains, startsWith, endsWith, greaterThan, lessThan, greaterOrEqual, lessOrEqual, between (value = [min, max]), isEmpty, isNotEmpty, isTrue, isFalse, matchesRegex (value = pattern), in, notIn (value = array), arrayContains, lengthGreaterThan, lengthLessThan, dateAfter, dateBefore (value = a date, 'today' or 'now'), withinLastDays, olderThanDays (value = number of days). Leave empty to keep every row (transform-only mode). 'caseSensitive' can be set per-condition to override the global default below; for matchesRegex only a per-condition 'caseSensitive': true makes it case-sensitive. Dotted paths like 'address.city' work in 'field'.

Type:array

Combine filters with

filterCombineMode

Optional

AND: a row must pass every condition. OR: a row passes if it matches any one condition.

Type:string

Default:AND

Options:

ANDOR

Case-sensitive filters by default

caseSensitiveFilters

Optional

Off (default) treats 'US', 'us' and ' US ' as the same value for equals, notEquals, contains, notContains, startsWith, endsWith, in, notIn and arrayContains, which is what scraped or hand-entered data usually needs. Turn on to match letter case exactly. This is not byte-for-byte: surrounding spaces are still trimmed and repeated spaces collapsed, and equals, notEquals, in, notIn and arrayContains still compare two values that both read as numbers as numbers ('1,200' equals 1200 while 'Lenient numbers' is on). matchesRegex ignores this switch and stays case-insensitive unless that condition sets 'caseSensitive': true. Override per-condition with a 'caseSensitive' key on that condition.

Type:boolean

Default:false

Lenient numbers

lenientNumbers

Optional

Read numbers stored as text, like '$1,234.50', '49 USD' or '(300)', as numbers for numeric filters, sorting, 'cast to number', 'round' and 'compute'. Scraped prices almost always need this. Turn off to only accept real numbers and plain numeric strings.

Type:boolean

Default:true

Sort by

sortBy

Optional

Order the kept rows. Each entry is {"field": "revenue", "direction": "desc"} or the shorthand "-revenue" (a leading minus means descending). Several entries sort by the first, then the next. Numbers sort numerically (with lenient parsing), text sorts case-insensitively, blanks always go last.

Type:array

Keep one row per distinct value of

distinctBy

Optional

Field names. Only the first kept row for each distinct combination of these fields is written out; later duplicates are dropped (matched case-insensitively, trimmed, with '$1,200' and 1200 treated as equal). Combine with 'Sort by' to choose which duplicate survives, e.g. sort by date descending and dedupe by email to keep the newest row per email.

Type:array

Maximum rows to output

limit

Optional

Stop after this many kept rows (after sorting and deduping). Useful for 'top 100 by price' style results and as a cost cap.

Type:integer

Minimum:1

Skip the first N rows

offset

Optional

Skip this many kept rows before writing (after sorting and deduping), for paging through a large result.

Type:integer

Minimum:0

Also append to a named dataset

outputDatasetName

Optional

Optional. A name (3 to 63 letters, digits or hyphens, e.g. 'clean-leads'). The kept rows are appended to a dataset with this name in your account, created on the first run, so a scheduled pipeline accumulates into one place instead of one dataset per run. Not charged again.

Type:string

Export file formats

exportFormats

Optional

Also save the kept, transformed rows as a real downloadable file in the run's key-value store. CSV opens anywhere; XLSX opens in Excel and Google Sheets with a bold, frozen header row.

Type:string[]

Maximum input rows

maxItems

Optional

Stop loading after this many rows from the dataset or file (a cost guard for large inputs). There is a hard safety ceiling of 200,000 rows per run regardless.

Type:integer

Minimum:1

Webhook URL (optional)

webhookUrl

Optional

Optional. If set, the kept and transformed rows (plus download links and a summary) are POSTed here as JSON the moment this run finishes, so you don't have to come back and check the dataset yourself. Works with a Zapier/Make/n8n catch-hook, your own API endpoint, or a Slack incoming webhook. Only charged when the endpoint actually confirms receipt (HTTP 2xx); a failed delivery is reported as a warning in the run's output and costs nothing.

Type:string

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