Paper Title
Exploratory Data Analysis of Indian Schools Statistics

Abstract
It’s important to note that education is an essential part of human life and evolution. Knowing the depths of the Indian educational system is vital to developing effective policies and improving the quality of education there. This paper aims to explore Indian Schools Statistics (ISES) data by using Python’s data science toolkit as a tool for analyzing it. The analysis covered different educational indicators like enrollment rates, dropout rates, and school facilities which include toilets, electricity, computers, and water. Using libraries such as Numpy, Pandas, Matplotlib, and Seaborn in Python programming language the study looked at patterns and trends in educational performance that highlighted regional disparities and the influence of socio-economic factors. These findings are important for policymakers and educators who intend to tackle educational inequities and improve student learning outcomes. Keywords - Exploratory Data Analysis, Indian Schools Statistics, Regional Disparities, Python Data Science, Education Indicators, Quantitative Analysis, Data Visualization