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By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.
Columns with an atomic data type (e.g., numeric, varchar or datetime columns) can be designated as sparse simply by including the word SPARSE in the column definition of the CREATE TABLE statement. Sparse columns optimize the storage of NULL values (which now take up no space at all) and are useful when the majority records in a table will have ...
In computer science, a hash table is a data structure that implements an associative array, also called a dictionary or simply map; an associative array is an abstract data type that maps keys to values. [2] A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired ...
A tri-temporal database has three axes of time: Valid time; Transaction time; Decision time; This approach introduces additional complexities. Temporal databases are in contrast to current databases (not to be confused with currently available databases), which store only facts which are believed to be true at the current time.
Directional-change intrinsic time is an event-based operator to dissect a data series into a sequence of alternating trends of defined size .. Figure 1: A financial market price curve (grey) dissected by a set of directional-changes (grey squares).