Visualization is the graphical representation of information and data. Using visual elements visualization tools helps understand trends, patterns and outliers in data with minimum complexity. There are two types of data visualizations, Univariate visualizations helps understand the distribution of a single variable and Multivariate visualization expresses the relationship between multiple variables. In a world of big data visualizations are crucial to make data-driven decisions by analyzing massive amounts of data. Many visualization methods such as scatter plots, bar charts, histograms, line charts, and pie charts, are widely used to tell stories removing the noise from data and zero in on the useful information. The better you convey your points visually, the better you can leverage that information.
Om Sehgal (2019); Visualizing data using Lattice in R and Seaborn in Python for data science; International Journal of Scientific and Research Publications (IJSRP)
9(12) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.9.12.2019.p9609