PAMI is a Python library containing 100+ algorithms to discover useful patterns in various databases across multiple computing platforms. (Active)
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A dense dataframe is basically a matrix in which the first column represents the row-identifier/timestamp and the remaining columns represent the items and their values. T
rowIdentifier/timestamp Item1 Item2 ... ItemN
| timestamp | Bread | Jam | Butter | Books | Pencil |
|---|---|---|---|---|---|
| 1 | 3 | 1 | 2 | 0 | 0 |
| 2 | 7 | 2 | 0 | 10 | 20 |
| 3 | 0 | 0 | 3 | 0 | 0 |
| 4 | 4 | 0 | 0 | 0 | 0 |
In the above dataframe (or table), the first transaction (or row) provides the information that a customer has purchased the 3 packets of Bread, 1 bottle of Jam, 3 packets of Butter at the timestamp of 1. The second transaction provides the information that a customer has purchased 7 packets of Bread, 2 bottles of Jam, 10 Books and 20 Pencils. Similar arguments can be made for the remaining transactions in the above dataframe.