Data Visualization Techniques
Caption: Data Visualization
Source: searchenginejournal
Exploration of data, understanding of data, and presenting the summary of the data in a beautiful way for further statistical analysis and interpretations are all the final outputs of data visualization. In the world of abundant data, visualization is essential frequently during the exploratory analysis and primary data cleaning processes in the field of machine learning, data science, and data mining. There are various techniques for data visualization which are further explored here:
1. Word Clouds
Caption: Word clouds for words used in a report
Source: Nelson Norman Group
Word Cloud is a visualization technique for texts done in static ways. In a word cloud, the most frequently used words are presented in larger font size and others are presented according to their frequency of appearances. It is used to summarize the contents of websites or text documents. There are typically 2 types of word cloud visualization: static and dynamic. A word cloud can be used as a primary visualization technique for NLP and other text related analyses. It has also been used by writers to make sure they are using the right words and frequency in their works.
2. Racing Bar Charts
Racing Bar Charts are spotted during games, stock market visualization, and hugely used during the Covid-19 Corona Pandemic throughout the world. It is the most easily understood and taken in interest visualization technique by even common people. Racing Bar charts are basically inverted bars showing the animation of timelines, races, and even stock market results. Flourish has officially released an easy application for such racing bar charts creation without coding, which only requires the data to be fed.
Caption: Racing Bar visualization for most popular websites
Source: Fiverr
3. Heat Maps / Correlation Matrix
Caption: Heat map visualization
Source: Excel-easy
Heat maps or correlation matrix are divided into a grid and within each square, the relative intensity of values as provided the raw data is presented. For easier analysis colors are used for visual perception. There are two types of heat maps: Spatial and cluster heat map. The color clusters are laid into the grids either hue and intensity property giving visual cues to the viewers. Through this, the patterns in the heat maps are interpreted for further analysis in machine learning, data mining, and cluster analysis. It is used for understanding the correlation of the data in the table and even spots out missing data in the table.
4. Treemaps
Using nested figures it displays the hierarchical data. According to the dimension of data, the node's rectangle area is displayed. Tiling algorithms are defined in order to develop a treemap.
6. Sankey Diagram
Caption: Sankey Diagram
Source: ipoint
Sankey diagram is a technique offering to see flow patterns and identify trends. It is a widely used inflow of customers in an eCommerce site. A Sankey diagram consists of nodes, links, and instructions to where nodes and links are to be placed. The major applications are oil flow analysis or energy analysis, customer flow navigations, and so on.
7. Network Diagram
Network diagrams are the data visualization techniques useful for semi or unstructured data, containing nodes and lines, which highlight the interconnection of the nodes. It is often used in studies of the social network over internets, and during the academic studies in computer science in various algorithms like A* heuristic search algorithms, depth-first search algorithms, and so on. Even during operating system analysis for scheduling the tasks, DAG diagrams, a type of network diagram is utilized.
Caption: Network Diagram
Source: data-to-viz
8.Charts
Caption: Bubble Chart
Source: mindtools
Under the charts, various data visualization techniques are used widely such as bar charts, bubble charts, pie charts, box plots, histograms, line graphs, and cartesian graphs. They are useful in the presentation of reports and surveys, which is easily understood by common people.
Caption: Bar Chart
Source: marketingcharts
Data visualization is powerful for primary analysis and providing visual cues. These are various techniques widely used for data visualization. Others that remain unopened here are mind mapping, plots like scatter plots, and so on. As said by John W. Tuckey, " The greatest value of a picture is when it forces us to notice what we never expected to see", and this leaves the significance of data visualization.
Comments