Data Visualization in RapidMiner
Data Visualization in RapidMiner
What makes life easy for communicating results for Data Scientists to various stakeholders is Data Visualization. Various tools are used for data visualizations, but Rapid Miner is a tool where a Data Scientist not only builds excellent ML models, but also a great tool for data visualization. There are different views such as data view, statistics, charts, and advanced charts to visualize data in RapidMiner. Once we upload the data in RapidMiner, the dataset is ready for visualization. Each row is called an example and columns are called attributes. There are different regular attributes and one special attribute (green color) in the data window. The special attribute is called label, and this attribute is to be predicted using other regular attributes. Columns could be selected in ascending or descending pattern. In the top right corner, some pre-defined filters are there to check if there are any missing values and labels in the data.
Some basic statistics are displayed, such as count for non-numeric columns and min, max and average for numeric columns. Data type is also defined for each column.
Basic visualization can be done by clicking on the arrows for the attribute names.
For the detailed view for the statistics of each attribute, we need to click on the open visualization for the specific attribute.
To compare one attribute with another attribute, we need to click on the value columns and select columns we are interested in.
Data Grouping is also possible based on the distribution of attributes.
These are some of the visualizations shown here using RapidMiner. The most exciting part of this tool is you don’t have to write any code for those visualizations. For similar visualizations, feel free to download the student edition, which is available to all students free of cost.