Adatkészletáttekintés

Adatkészletáttekintés is a Hungarian term that translates to "dataset overview" or "data set summary" in English. It refers to the process of examining and understanding the fundamental characteristics of a dataset. This initial exploration is a crucial step in data analysis, machine learning, and data science workflows. The primary goal of an adatkészletáttekintés is to gain insights into the data's structure, content, and quality before proceeding with more complex modeling or manipulation.

Key aspects of an adatkészletáttekintés typically include understanding the number of observations (rows) and variables (columns), identifying the data types of each variable (e.g., numerical, categorical, text), and summarizing the range and distribution of numerical variables through measures like mean, median, minimum, maximum, and standard deviation. For categorical variables, frequencies and proportions are often examined. Visualizations such as histograms, box plots, and scatter plots are commonly employed during this phase to reveal patterns, outliers, and potential relationships between variables.

Furthermore, an adatkészletáttekintés involves assessing data quality. This includes identifying missing values, detecting duplicate records, and spotting inconsistencies or errors in the data. Understanding these aspects helps in deciding on appropriate data cleaning and preprocessing strategies, which are essential for ensuring the reliability and validity of subsequent analyses. A thorough adatkészletáttekintés provides a solid foundation for making informed decisions throughout the data analysis lifecycle.