10.46243/jst.2022.v7.i09.pp01-11 registered
Graphical Exploratory Data Analysis (GEDA): A Case Study on Employee Attrition
Resolves to https://www.jst.org.in/index.php/pub/article/view/838
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2022.v7.i09.pp01-11
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 145df8e38f932a30…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Graphical Exploratory Data Analysis (GEDA): A Case Study on Employee Attrition (PrincipalTitle)
Published 2022-05-11
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 7 · issue 9 · pages 1–11
Agents
- Dr. Ayesha Banu Dr. Ayesha Banu (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2022.v7.i09.pp01-11
Abstract
Exploratory Data Analysis (EDA) popularly performs some preliminary investigations on the dataset to understand its content and structure. EDA is a mandatory step in the complete process of data analysis, since its mandatory to analyze the data in order to produce good results and in turn help in decision making. There are several Graphical EDA techniques which not only analyze the data but also present the results in graphical form. This paper uses the Python programming language for both data analysis and visualization of results. The rich set of python libraries including pandas, numpy, matplotlib, seaborn etc greatly supports the process of GEDA. This paper works on the “Employee Performance and Attrition” dataset to analyze and extract potential information and present results in graphical form
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Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2022.v7.i09.pp01-11 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Graphical Exploratory Data Analysis (GEDA): A Case Study on Employee Attrition (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Dr. Ayesha Banu Dr. Ayesha Banu publisher: Longman Publishers published: 2022-05-11 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 9 · pp. 1–11 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2024-02-16 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
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Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 87 fields set · sha256 457a88874906… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
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