Visualization is the graphic representation of data through the use of pictorial design. The goal is to make a visual easy to comprehend and presentable. In general, visualization in data science can be divided into univariate and multivariate data visualizations. Univariate data visualization involves plotting a single variable to understand more about its distribution while multivariate plots express the relationship between two or more variables. The usual data visualization methods, such as scatter plots, bar charts, histograms, line charts, and pie charts, are widely used in management research. In a world of rapid evolution of data science, however, new techniques to visualize quantitative and qualitative data is what everyone is looking for.
Arnav Oberoi, Rahul Chauhan (2019); Visualizing data using Matplotlib and Seaborn libraries in Python for data science; International Journal of Scientific and Research Publications (IJSRP)
9(3) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.9.03.2019.p8733