Data Visualization Techniques In Data Science. Data visualization is a process of representing data in a graphical format by using different visual elements such as charts tables graphs maps infographics etc. Data visualization is used in many areas to model complex events and visualize phenomena that cannot be observed directly such as weather patterns medical conditions or mathematical relationships.
It helps the customer and business user for understanding their data. It is a. A method for graphically depicting groups of numerical data through their quartiles.
Data science comprises of multiple statistical solutions in solving a problem whereas visualization is a technique where data scientist use it to analyze the data and represent it the endpoint.
Healthcare professionals frequently use choropleth maps to visualize important health data. While such data visualization techniques are extremely useful for depicting the values from a single data set they are of little help when comparing two or more different sets. It is very user friendly drag and drop tool and create different sorts of visualization with the data citation mak l 1033 the key deliverable for this research project will be. Another common visualization technique is a scatter plot that is a two dimensional plot representing the joint variation of two data items.
