Abstract : Data scientists and analysts can analyze, display, and get important insights from their datasets through exploratory data analysis (EDA), a critical phase in the data analysis process. With its extensive data manipulation and visualization module ecosystem, Python has become a potent tool in this situation. This chapter provides a thorough introduction of Python-based EDA techniques, highlighting the value of EDA in the pipeline for data analysis and presenting different approaches to data visualization, summary statistics, and statistical testing.
Keywords : Exploratory Data Analysis, EDA, Python, Data Analysis, Data Visualization, Summary Statistics, Data Exploration, Data Insights, Data Science
Cite : Gouri, M. H., & Nafees, M. (2023). EXPLORATORY DATA ANALYSIS USING PYTHON (1st ed., p. 28). Noble Science Press. https://doi.org/10.52458/9789388996747.nsp2023.eb.ch-04
References :
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