Exploratory Data Analysis
Exploratory Data Analysis is a systematic approach within data analytics that employs descriptive statistics and visualization techniques to examine, summarize, and uncover underlying patterns, anomalies, or structural features in datasets prior to formal modeling, distinguishing it from confirmatory or predictive analytics by its hypothesis-generating, open-ended nature.
1.4K
Publications
223.4K
Citations
3.1K
Authors
1.1K
Institutions
Publications per year
2017–2026
445
Variants
Eda
1.4K
1–5 of 1.4K
3.1K
12
h-index
11
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11
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9
h-index
1–5 of 3.1K
1.1K
University of California, Berkeley
Berkeley, United States
17 h-index
44 publications
3.4K citations
Stanford University
Stanford, United States
16 h-index
42 publications
9K citations
University of Michigan
Ann Arbor, United States
16 h-index
34 publications
7.4K citations
University of Maryland, College Park
College Park, United States
16 h-index
47 publications
3.8K citations
Carnegie Mellon University
Pittsburgh, United States
14 h-index
33 publications
1.3K citations
University of Cambridge
Cambridge, United Kingdom
14 h-index
36 publications
3.2K citations
University of Washington
Seattle, United States
13 h-index
27 publications
1.9K citations
University of Illinois Urbana-Champaign
Urbana, United States
13 h-index
36 publications
2.4K citations
1–8 of 1.1K
TVCG · 32 publications · 2.6K citations
25
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31 publications · 3.1K citations
20
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JCGS · 22 publications · 18.3K citations
18
h-index
20 publications · 1.5K citations
16
h-index
25 publications · 3.5K citations
16
h-index
1–5