ANALYSIS OF NFHS V DISTRICT-WISE DATA USING MLAND POWER BI

Abstract

This study harnesses machine learning methodologies, with a focus on regression models, integrated into Power BI for the analysis of district-wise data extracted from the National Family Health Survey (NFHS) V. Emphasizing women's empowerment as the central theme, India is divided into zones to discern regional nuances. It determines the condition of women in society at different levels like districts, states and zone so that the required changes can be made at each level. The data has been taken from an official government website http://www.data.gov.in . which vouch for its authenticity. Also, finding the parameters which can lead to women empowerment in society. The insights from the data were analyzed using Python libraries like NumPy, Pandas, Scikit Learn and statsmodel.api. The Power BI and MS Excel’s Pivot table were used to visualize the findings. We have also analyzed how access to basic amenities affect literacy rate by using different regression models. The parameters considered in this study were the ones that would most likely contribute to the situation of women in society. This study will explore each point in detail and its impact on women’s status