Study on Exploratory Data Analysis Applied to Education

Data mining has had a wide application in the educational field. This discipline seeks to analyze the data generated in educational environments to improve teaching processes and predict academic performance. Exploratory data analysis is a key stage of data mining, where statistics and graphical tools are used to understand the data, identify errors, detect outliers, and find relationships between variables. In Mexico, the analysis of educational achievement in upper secondary education represents an important area of study due to the large number of young people who attend this educational level, but also due to the high dropout rate at the higher level. The objective of this research is to analyze, through data exploration, the significant variables of academic achievement of high school students in the state of Veracruz. The method considers from the description of the data structure, the identification of missing and atypical data as well as the relationships between pairs of variables. For this, the Google Colaboratory tool was used to write and execute Python code and import the necessary libraries such as Pandas, Numpy, Matplotlib and Seaborn. It can be concluded that by not finding null values in the data, the integrity of the analysis is guaranteed; Data analysis through histograms allowed conclusions to be drawn about the dispersion, concentration, and extreme values of the data, providing valuable information, since they allow them to adjust teaching techniques, education segmentation, and tools to meet the needs of high school students. top in state.