Paper Title
Movies and TV Shows – Exploratory Data Analysis (EDA) and Visualization Using Python
Article Identifiers
Authors
Salim Umar Ladan , Stephen Ladu Sebit Amosa , Eseto Lomumba Patric , Salim Isah , Maryam Abubakar Yazid
Keywords
Python, Data Science, Data Analysis, Pandas, Data Visualization, Matplotlib, Seaborn.
Abstract
The Movies dataset analysis focuses on identifying trends in consumer habits and preferences regarding the streaming service. It examines the viewing history of subscribers, the types of content they watch, the time spent watching, and the geographic area of the audience. The data is gathered from various sources, including surveys, reviews, and marketing campaigns. Through careful data analysis, researchers can uncover valuable insights on the behavior of Movies subscribers and the effectiveness of the service The analysis can provide valuable guidance for making decisions about content creation. marketing strategies, and pricing models. The results of the analysis can be used to improve the customer experience and increase customer loyalty
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How To Cite (APA)
Salim Umar Ladan, Stephen Ladu Sebit Amosa, Eseto Lomumba Patric, Salim Isah, & Maryam Abubakar Yazid (May-2024). Movies and TV Shows – Exploratory Data Analysis (EDA) and Visualization Using Python. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), g294-g305. https://ijnrd.org/papers/IJNRD2405635.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : g294-g305
Other Publication Details
Paper Reg. ID: IJNRD_222427
Published Paper Id: IJNRD2405635
Downloads: 000121980
Research Area: Computer Science & TechnologyÂ
Country: Raipur , Chhattisgarh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405635.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405635
About Publisher
Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.
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Current Issue: Volume 10 | Issue 10 | October 2025
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