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Data Wrangling and Preparation Tools

A directory of tools for cleaning, transforming and preparing raw data — open-source libraries, self-service preparation tools, enterprise platforms and web data extraction.

30 topics•5 categories•Updated November 2026

Open-source Libraries & Tools

4 entries

Code-first and free tools for data preparation.

01OpenRefineA powerful free, open-source tool for working with messy data: cleaning it, transforming it, and extending it with web services. 02pandasPython library for data analysis and manipulation. 03PolarsFast DataFrame library written in Rust, with Python bindings. 04DuckDBIn-process analytical SQL database that reads files such as CSV and Parquet directly.

Self-service Data Preparation

6 entries

Point-and-click preparation for analysts.

05Microsoft Power QueryThe easiest way to connect, extract, transform, and load data from a wide range of sources across Excel, Power BI, and beyond. 06Rapidminer Monarch (Siemens)A market-leading desktop-based self-service data preparation solution that connects to structured, unstructured, cloud, and big data sources. 07Alteryx AutomationThe Alteryx platform delivers end-to-end automation of analytics, machine learning, and data science processes, enabling agility at scale. 08Talend Data Preparation (now part of Qlik)A self-service, browser-based, point-and-click tool to quickly identify errors and apply reusable, shareable data cleansing rules. 09Tableau DesktopDelivers everything you need to connect, prepare, visualize, and analyze your data with drag-and-drop simplicity. 10Datameer XMakes it easy for data engineers to ingest and export structured and unstructured data in and out of a data lake, with a familiar spreadsheet interface.

Enterprise Data Preparation & Enrichment

3 entries

Platforms for governed, large-scale preparation.

11Precisely Data360 AnalyzeEmpowers users to discover and share insights faster with self-service data prep and analytics on an intuitive, browser-based platform. 12Tamr Data EnrichmentCurates and actively manages external datasets and services, embedding trusted, high-quality referential data into your mastering pipeline. 13Cambridge Semantics Anzocambridgesemantics.com now redirects to Siemens' RapidMiner page.

Web Data Extraction

2 entries

Collect data from websites.

14ScrapyThe world's most-used open-source data extraction framework for Python, built for fast, scalable web crawling. 15ParseHubA free and powerful web scraping tool — extracting data is as easy as clicking on the data you need.

Open Wrangling Tools

6 entries

Open tools.

16pandasData analysis library. 17PolarsFast DataFrame library. 18DuckDBIn-process analytical database. 19OpenRefineData cleaning tool. 20dbtSQL transformation framework. 21Apache ArrowIn-memory columnar format.

Related Pages

9 entries

Related directories on this site.

22Data ScienceData science hub. 23Data Science PlatformsEnd-to-end data science platforms. 24Data Science IDEsNotebook and IDE tools. 25Data Sets for ML/DLDatasets for training and benchmarking. 26Websites to Learn Data ScienceLearning websites. 27Machine LearningMachine learning hub. 28ETL and ELT ToolsOpen-source ETL, dbt, enterprise ETL, cloud ETL and managed ELT. 29Software Tools DirectoryHub of tool directories across AI, DevOps, observability, data and security. 30Data EngineeringHub of data engineering, pipeline, lakehouse and streaming resources.

Frequently Asked Questions

What is data wrangling?

Data wrangling is the process of cleaning, structuring and enriching raw data so it is ready for analysis or machine learning.

Why does it take so long?

Real data is messy: missing values, inconsistent formats and duplicates need fixing, and most data science projects spend much of their time on this step.

Code or no-code?

Libraries such as pandas and Polars give full control and reproducibility; tools like Power Query and OpenRefine let analysts clean data interactively.

Where does web scraping fit?

Scrapy and ParseHub collect data from websites; always check a site's terms and robots rules first.

How does this differ from data ingestion?

Ingestion moves data into your environment; wrangling prepares it once it is there.

Which related standards, open tools and references does this page add?

The section 'More Wrangling Tools' lists OpenRefine, pandas, Polars, DuckDB. Open tools.

Where can I find more tool directories?

The Software Tools Directory page links to curated directories across AI and ML, DevOps, observability, data, security and developer tooling.

Which additional references does this page add?

The section 'Open Wrangling Tools' lists pandas, Polars, DuckDB, OpenRefine, dbt.

Which links may need a manual click?

Links were rechecked in October 2026. Datameer and Tableau returned 403 to automated checks and are kept; they may need a manual click. For loading and transformation tools, see ETL and ELT Tools on this site.