Methods and apparatus to partition data
Methods and apparatus to partition data are disclosed. An example apparatus to partition panelist data includes an indicator matrix generator to determine an indicator matrix including panelist vectors for panelists based on panelist data associated with the panelists, a first one of the panelist vectors for a first one of the panelists to indicate whether the first one of the panelists: has a first characteristic, meets a first criterion based on the first characteristic and a second characteristic, has a third characteristic, and meets a second criterion based on the third characteristic and a fourth characteristic. The example apparatus further includes a matrix reducer to reduce the indicator matrix to a set of unique panelist vectors that represent partitions of the panelist data, the partitions of the panelist data to utilize less storage capacity than the panelist data.
1. An apparatus to partition panelist data, the apparatus comprising:
at least one memory;
computer readable instructions; and
at least one processor to execute the computer readable instructions to at least:
store panelist data in the at least one memory, the panelist data collected from at least one thousand panelists;
determine an indicator matrix including panelist vectors for panelists based on the panelist data, the panelist data associated with the panelists, a first one of the panelist vectors for a first one of the panelists to indicate whether the first one of the panelists:
has a first characteristic;
meets a first criterion based on the first characteristic and a second characteristic;
has a third characteristic; and
meets a second criterion based on the third characteristic and a fourth characteristic;
identify a set of unique panelist vectors that represent partitions of the panelist data;
weight and store the set of unique panelist vectors in the at least one memory, respective ones of the stored unique panelist vectors to be weighted by corresponding numbers of the panelists represented by the respective ones of the stored unique panelist vectors; and
discard redundant remaining ones of the panelist vectors not included in the set of unique panelist vectors and discard the panelist data from the at least one memory to reduce a data storage requirement of the at least one memory.
2. The apparatus of claim 1 , wherein the at least one processor is to assign labels to the unique panelist vectors.
3. The apparatus of claim 2 , wherein the at least one processor is to:
store the labels assigned to the unique panelist vectors in the at least one memory.
4. The apparatus of claim 2 , wherein the at least one processor is to attach respective descriptions to the unique panelist vectors, the descriptions to indicate whether respective ones of the unique panelist vectors have the first characteristic, the second characteristic, the third characteristic and the fourth characteristic.
5. The apparatus of claim 2 , wherein the at least one processor is to assign panelist labels to the panelists, the panelist labels corresponding to the labels assigned to the unique panelist vectors.
6. The apparatus of claim 5 , wherein the at least one processor is to sort the panelists into groups corresponding to the panelist labels assigned to the panelists.
7. The apparatus of claim 1 , wherein the at least one processor is to determine the first criterion and the second criterion based on characteristics exhibited by a number of the panelists.
8. A method to partition panelist data, the method comprising:
storing, by executing an instruction with a processor, panelist data in at least one memory, the panelist data collected from at least one thousand panelists;
determining, by executing an instruction with the processor, an indicator matrix including panelist vectors for panelists based on the panelist data, the panelist data associated with the panelists, a first one of the panelist vectors for a first one of the panelists to indicate whether the first one of the panelists:
has a first characteristic;
meets a first criterion based on the first characteristic and a second characteristic;
has a third characteristic; and
meets a second criterion based on the third characteristic and a fourth characteristic;
identifying, by executing an instruction with the processor, a set of unique panelist vectors that represent partitions of the panelist data;
weighting and storing, by executing an instruction with the processor, the set of unique panelist vectors in the at least one memory, respective ones of the stored unique panelist vectors being weighted by corresponding numbers of the panelists represented by the respective ones of the stored unique panelist vectors; and
discarding, by executing an instruction with the processor, redundant remaining ones of the panelist vectors not included in the set of unique panelist vectors and discarding the panelist data from the at least one memory to reduce a data storage requirement of the at least one memory.
9. The method of claim 8 , further including assigning labels to the unique panelist vectors.
10. The method of claim 9 , further including:
storing the labels assigned to the unique panelist vectors in the at least one memory.
11. The method of claim 9 , further including attaching respective descriptions to the unique panelist vectors, the descriptions indicating whether respective ones of the unique panelist vectors have the first characteristic, the second characteristic, the third characteristic and the fourth characteristic.
12. The method of claim 9 , further including assigning panelist labels to the panelists, the panelist labels corresponding to the labels assigned to the unique panelist vectors.
13. The method of claim 12 , further including sorting the panelists into groups corresponding to the panelist labels assigned to the panelists.
14. The method of claim 8 , further including determining the first criterion and the second criterion based on characteristics exhibited by a number of the panelists.
15. A tangible computer readable storage medium comprising instructions that, when executed, cause a machine to at least:
store panelist data in at least one memory, the panelist data collected from at least one thousand panelists;
determine an indicator matrix including panelist vectors for panelists based on the panelist data, the panelist data associated with the panelists, a first one of the panelist vectors for a first one of the panelists to indicate whether the first one of the panelists:
has a first characteristic;
meets a first criterion based on the first characteristic and a second characteristic;
has a third characteristic; and
meets a second criterion based on the third characteristic and a fourth characteristic;
identify a set of unique panelist vectors that represent partitions of the panelist data;
weight and store the set of unique panelist vectors in the at least one memory, respective ones of the stored unique panelist vectors to be weighted by corresponding numbers of the panelists represented by the respective ones of the stored unique panelist vectors; and
discard redundant remaining ones of the panelist vectors not included in the set of unique panelist vectors and discard the panelist data from the at least one memory to reduce a data storage requirement of the at least one memory.
16. The tangible computer readable storage medium of claim 15 , wherein the instructions further cause the machine to assign labels to the unique panelist vectors.
17. The tangible computer readable storage medium of claim 16 , wherein the instructions further cause the machine to:
store the labels assigned to the unique panelist vectors in the at least one memory.
18. The tangible computer readable storage medium of claim 16 , wherein the instructions further cause the machine to attach respective descriptions to the unique panelist vectors, the descriptions indicating whether respective ones of the unique panelist vectors have the first characteristic, the second characteristic, the third characteristic and the fourth characteristic.
19. The tangible computer readable storage medium of claim 16 , wherein the instructions further cause the machine to assign panelist labels to the panelists, the panelist labels corresponding to the labels assigned to the unique panelist vectors.
20. The tangible computer readable storage medium of claim 19 , wherein the instructions further cause the machine to sort the panelists into groups corresponding to the panelist labels assigned to the panelists.