Data wrangling

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Background

United States Library of Congress National Digital Information Infrastructure and Preservation Program Emory University Jargon File Data

12 related topics

Modus operandi

KNIME Python SQL Recommenders Programming by example

9 related topics

Core ideas

Data discovery Structuring Cleaning Null values Validation

6 related topics

Connection to data mining

Data mining Texas Houston Dallas

4 related topics

Topics to explore

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Overview

Mapping data Data mapping
Raw Raw data
Format Content format
Munging Mung (computer term)
Data visualization
Data aggregation
Statistical model
ETL Extract, transform, load

Background

Connection to data mining

Core ideas

Data discovery
Structuring Data structuring?action=edit&redlink=1
Cleaning Data cleaning
Null values Null (SQL)
Validation Data validation
Data consistency

Typical use

Data architects Data architect
Data warehouses Data warehouse
Data lakes Data lake

Modus operandi

Advanced semantic analysis

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Map overview Semantic statistics

Nodes49

Edges48

Triples74

Avg. degree1.96

Density0.040816

Components1

How this topic connects Entity context

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Data wrangling

Top relations

related to background · 16

Data wrangling → Cline, Congress's National Digital Information, Donald Cline, Emory University Libraries, Experiment, In, Infrastructure, Jargon File, MetaArchive Partnership, NASA/NOAA Cold Lands Processes, NDIIPP, One, Preservation Program, The, This, United States Library

related to Modus operandi · 15

Data wrangling → AI, Data, Depending, Early, Excel, KNIME, OpenRefine, PHP, Python, Scala, Some, SQL, Stanford/Berkeley Wrangler, Trifacta, Visual

related to Core ideas · 12

Data wrangling → An, Be, Cleaning There, Data, Enriching At, Publishing Prepare, Raw, Structuring The, The, This, Use, Validating This

related to Connection to data mining · 8

Data wrangling → An, Dallas, Data, Even, Houston, Texas, The, US

related to Example · 5

Data wrangling → Are, Before, Given, Once, Start

related to External links · 4

Data wrangling → Benefits, My Influencer Journey, Retrieved, What

related to Benefits · 3

Data wrangling → Analysis, By, Well-designed

is a · 1

Data wrangling → superset of data mining does not mean that data mining does not use it

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

data wrangling process set munging step include typically mining example also use could steps analysis raw wrangler validation term tools

Entity relationships Subject–Predicate–Object triples

Subject	Predicate	Object	Confidence	Src
Data wrangling	is a	superset of data mining does not mean that data mining does not use it	0.90	text
analytics	instance of	data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes	0.80	text
Wrangler generate editable histories	instance of	interactive systems	0.80	text
auditable transformation scripts	instance of	interactive systems	0.80	text
reducing manual	instance of	interactive systems	0.80	text
one-off editing.Efficiency	instance of	interactive systems	0.80	text
reuse	instance of	interactive systems	0.80	text
data warehouses	instance of	or systems that will further process the data and write it into targets	0.80	text
data lakes	instance of	or systems that will further process the data and write it into targets	0.80	text
or downstream applications	instance of	or systems that will further process the data and write it into targets	0.80	text
Excel	instance of	e.g. via spreadsheets	0.80	text
Data wrangling	related to background	The	0.60	section

Related concept clusters Concept neighborhoods

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Connections between topic areas Semantic bridges

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Min side: 3

Research this topic

Explore this topic

Background

Modus operandi

Core ideas

Connection to data mining

Key facts & relationships

Topics to explore

Overview

Background

Connection to data mining

Core ideas

Typical use

Modus operandi

Advanced semantic analysis

Map overview Semantic statistics

Data wrangling

How this topic connects Entity context

Data wrangling

Top relations

Important terminology Word statistics

Important terminology

Entity relationships Subject–Predicate–Object triples

Related concept clusters Concept neighborhoods

Connections between topic areas Semantic bridges