Systems and methods for visualization of data analysis
Exemplary systems and methods for visualization of data analysis are provided. In various embodiments, a method comprises accessing a database, analyzing the database to identify clusters of data, generating an interactive visualization comprising a plurality of nodes and a plurality of edges wherein a first node of the plurality of nodes represents a cluster and an edge of the plurality of edges represents an intersection of nodes of the plurality of nodes, selecting and dragging the first node in response to a user action, and reorienting the interactive visualization in response to the user action of selecting and dragging the first node.
1. A method comprising:
receiving data points, each data point including two or more features;
mapping each of the data points to a mathematical reference space using a mathematical filter function, each data point being represented once in the mathematical reference space;
generating a cover of open sets in the mathematical reference space, each data point in the mathematical reference space being in at least one of the open sets;
performing at least one similarity function on at least one data point based on data associated with at least one of the open sets of the cover in the mathematical reference space to determine one or more nodes of a plurality of nodes, each of the one or more nodes of the plurality of nodes comprising members representative of at least one subset of the data points;
generating a visualization comprising the plurality of nodes and a plurality of edges wherein each of the edges of the plurality of edges connects nodes with shared members;
receiving a selection of a first node of the plurality of nodes in response to a user action; and
displaying information associated with at least one feature of at least one data point that is a member of the first node.
2. The method of claim 1 , further comprising receiving a selection of a second node of the plurality of nodes.
3. The method of claim 2 , further comprising displaying information associated with at least one feature of at least one data point that is a member of the second node, the information associated with at least one feature of at least one data point that is a member of the second node being displayed at the same time that the information associated with at least one feature of at least one data point that is a member of the first node is displayed.
4. The method of claim 1 , further comprising receiving a selection of data identifiers, each data identifier of the selection of data identifiers identifying different data points, the data points being received from at least one data structure, each of the data identifiers identifying different data points in the at least one data structure.
5. The method of claim 4 , further comprising displaying a highlight of at least one node in the visualization, the highlighted at least one node being identified by a data identifier of the selection of data identifiers.
6. The method of claim 1 , further comprising receiving a selection of a first function, wherein a first node and a second node of the plurality of nodes are colored differently in the visualization based on an application of the first function on any number of features of the data points.
7. The method of claim 1 , further comprising receiving an interval value and an overlap percentage of the cover, re-analyzing the data points based on the interval value and the overlap percentage, and regenerating the visualization based on the re-analysis.
8. The method of claim 3 , further comprising displaying statistical information in the visualization, the statistical information being based on features of data points that are members of the first node and a selected second node.
9. The method of claim 1 , wherein mapping the data to the mathematical reference space utilizes a geometric function as the filter function.
10. A non-transitory computer readable medium comprising instructions, the instructions being executable by a processor to perform a method, the method comprising:
receiving data points, each data point including two or more features;
mapping each of the data points to a mathematical reference space using a mathematical filter function, each data point being represented once in the mathematical reference space;
generating a cover of open sets in the mathematical reference space, each data point in the mathematical reference space being in at least one of the open sets;
performing at least one similarity function on at least one data point based on data associated with at least one of the open sets of the cover in the mathematical reference space to determine one or more nodes of a plurality of nodes, each of the one or more nodes of the plurality of nodes comprising members representative of at least one subset of the data points;
generating visualization comprising the plurality of nodes and a plurality of edges wherein each of the edges of the plurality of edges connects nodes with shared members;
receiving a selection of a first node of the plurality of nodes in response to a user action; and
displaying information associated with at least one feature of at least one data point that is a member of the first node.
11. The non-transitory computer readable medium of claim 10 , the method further comprising receiving a selection of a second node of the plurality of nodes.
12. The non-transitory computer readable medium of claim 11 , the method further comprising displaying information associated with at least one feature of at least one data point that is a member of the second node, the information associated with at least one feature of at least one data point that is a member of the second node being displayed at the same time that the information associated with at least one feature of at least one data point that is a member of the first node is displayed.
13. The non-transitory computer readable medium of claim 10 , the method further comprising receiving a selection of data identifiers, each data identifier of the selection of data identifiers identifying different data points, the data points being received from at least one data structure, each of the data identifiers identifying different data points in the at least one data structure.
14. The non-transitory computer readable medium of claim 13 , the method further comprising displaying a highlight of at least one node in the visualization, the highlighted at least one node being identified by a data identifier of the selection of data identifiers.
15. The non-transitory computer readable medium of claim 10 , the method further comprising receiving a selection of a first function, wherein a first node and a second node of the plurality of nodes are colored differently in the visualization based on an application of the first function on any number of features of the data points.
16. The non-transitory computer readable medium of claim 10 , the method further comprising receiving an interval value and an overlap percentage of the cover, re-analyzing the data points based on the interval value and the overlap percentage, and regenerating the visualization based on the re-analysis.
17. The non-transitory computer readable medium of claim 12 , the method further comprising displaying statistical information in the visualization, the statistical information being based on features of data points that are members of the first node and a selected second node.
18. The non-transitory computer readable medium of claim 10 , wherein mapping the data to the mathematical reference space utilizes a geometric function as the filter function.
19. A system comprising:
a processor;
memory including instructions being executable by the processor to control the processor to:
receive data points, each data point including two or more features;
map each of the data points to a mathematical reference space using a mathematical filter function, each data point being represented once in the mathematical reference space;
generate a cover of open sets in the mathematical reference space, each data point in the mathematical reference space being in at least one of the open sets;
perform at least one similarity function on at least one data point based on data associated with at least one of the open sets of the cover in the mathematical reference space to determine one or more nodes of a plurality of nodes, each of the one or more nodes of the plurality of nodes comprising members representative of at least one subset of the data points;
generate visualization comprising the plurality of nodes and a plurality of edges wherein each of the edges of the plurality of edges connects nodes with shared members;
receive a selection of a first node of the plurality of nodes in response to a user action; and
display information associated with at least one feature of at least one data point that is a member of the first node.