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Supported data types

This section provides details on the data types used within KDB.AI tables, including name, range/example, brief description, and usage.

In KDB.AI, tables are fundamental structures for storing and organizing data. Here’s a list of supported data types (pytype) in KDB.AI tables:

Pytype Range/example Description Usage
bool True/False Binary value Logical operations and conditions
str "Hello" Sequence of characters (letters, numbers, symbols, spaces) Textual data
uint8 0 to 255 Unsigned integer with 8 bits Memory-efficient storage in embedded systems
int16 -32,768 to 32,767 Signed integer with 16 bits. Larger integer values
int32 -2,147,483,648 to 2,147,483,647 Signed integer with 32 bits General-purpose integer arithmetic
int64 -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807 Signed integer with 64 bits Large integer computations
float32 3.14, 1.618 Single-precision floating-point number Real numbers with limited precision
float64 2.718281828459045 Double-precision floating-point number Provides higher precision than float32
bytes 0 to 255 (8 bits each) Sequence of bytes (raw binary data) Handling binary data, such as images or files
datetime64[ns] An offset from 1970-01-01T00:00:00 A date and time with nanosecond precision Timestamps and time-based calculations
timedelta64[ns] An extension of datetime64 with units such as (D)ay, (M)onth, (Y)ear, (h)ours, (m)inutes, or (s)econds Duration or time difference Measuring durations or time intervals