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# dtype
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## The goal
A numpy matrix can have differnt dtype or -- in other words -- differnt types of numbers with different precisions.
Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
## Signed integer types
**Please use numpy.int8, numpy.int16, numpy.int32, and numpy.int64 !!!**
* *numpy.int8*: 8-bit signed integer (-128 to 127). Compatible with C char.
* *numpy.byte*
* Character code 'b'
* *numpy.int16*: 16-bit signed integer (-32 768 to 32 767). Compatible with C short
* *numpy.short*
* Character code 'h'
* *numpy.int32*: 32-bit signed integer (-2 147 483 648 to 2 147 483 647). Compatible with C int
* *numpy.intc*
* Character code 'i'
* *numpy.int64*: 64-bit signed integer (-9 223 372 036 854 775 808 to 9 223 372 036 854 775 807). Compatible with Python int and C long
* *numpy.intp*
* *numpy.int_*
* Character code 'l'
*numpy.longlong*: Compatible with C long long
* Character code 'q'
## Unsigned integer types
**Please use numpy.uint8, numpy.uint16, numpy.uint32, and numpy.uint64 !!!**
* *numpy.uint8*: 8-bit unsigned integer (0 to 255). Compatible with C unsigned char.
* *numpy.ubyte*
* Character code 'B'
* *numpy.uint16*: 16-bit unsigned integer (0 to 65 535). Compatible with C unsigned short.
* *numpy.ushort*
* Character code 'H'
* *numpy.uint32*: 32-bit unsigned integer (0 to 4 294 967 295). Compatible with C unsigned int.
* *numpy.uintc*
* Character code 'I'
* *numpy.uint64*: 64-bit unsigned integer (0 to 18 446 744 073 709 551 615). Compatible with C unsigned long
* numpy.uint
* numpy.uintp
* Character code 'L'
* numpy.ulonglong: Compatible with C unsigned long long
* Character code 'Q'