Exploring Healthcare Trends: A Python-Powered Analysis of Doctor Visits
N. Nagalakshmi1, A. Sai Vishal2, P. Shiva Sai3, P. Karthik4
1Mrs. N. Nagalakshmi, Department of Information Technology, Anurag University, Hyderabad, India.
2Sai Vishal, Department of Information Technology, Anurag University, Hyderabad, India.
3P. Shiva Sai, Department of Information Technology, Anurag University, Hyderabad, India.
4P. Karthik, Department of Information Technology, Anurag University, Hyderabad, India.
Manuscript received on 12 March 2024 | Revised Manuscript received on 13 April 2024 | Manuscript Accepted on 15 April 2024 | Manuscript published on 30 May 2024 | PP: 1-4 | Volume-4 Issue-3 April 2024 | Retrieval Number: 100.1/ijdcn.E984013050424 | DOI: 10.54105/ijdcn.E9840.04030424
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This project delves into an analysis of the “Dr.Visits” dataset using Python tools and libraries, aiming to uncover insights into patterns and relationships related to doctor visits and health conditions. Through data visualization techniques and statistical methods, the projectseeksto reveal key trends and correlations within the dataset. Initial steps involve importing the dataset and exploring its characteristics, including variables like gender, age, income, and illness distribution. The analysis focuses on understanding how these variables impact doctor visits and health-related activities. Notably, the project highlights gender-based variations in reduced activity due to illness, prompting further exploration of potential contributing factors. In summary, this project provides valuable insights into healthcare and patient behavior through the lens of the “Dr.Visits” dataset.
Keywords: Data Analysis, Python Tools and Libraries, Data Visualization, Statistical Analysis, Behavior, Trends.
Scope of the Article: Data Visualization using IoT