numpy.array2string(a, max_line_width=None, precision=None, suppress_small=None, separator=' ', prefix='', style=<class 'numpy._globals._NoValue'>, formatter=None, threshold=None, edgeitems=None, sign=None, floatmode=None, suffix='', **kwarg)[source]

Return a string representation of an array.


a : ndarray

Input array.

max_line_width : int, optional

The maximum number of columns the string should span. Newline characters splits the string appropriately after array elements.

precision : int, optional

Floating point precision. Default is the current printing precision (usually 8), which can be altered using set_printoptions.

suppress_small : bool, optional

Represent very small numbers as zero. A number is “very small” if it is smaller than the current printing precision.

separator : str, optional

Inserted between elements.

prefix : str, optional

suffix: str, optional

The length of the prefix and suffix strings are used to respectively align and wrap the output. An array is typically printed as:

prefix + array2string(a) + suffix

The output is left-padded by the length of the prefix string, and wrapping is forced at the column max_line_width - len(suffix).

style : _NoValue, optional

Has no effect, do not use.

Deprecated since version 1.14.0.

formatter : dict of callables, optional

If not None, the keys should indicate the type(s) that the respective formatting function applies to. Callables should return a string. Types that are not specified (by their corresponding keys) are handled by the default formatters. Individual types for which a formatter can be set are:

- 'bool'
- 'int'
- 'timedelta' : a `numpy.timedelta64`
- 'datetime' : a `numpy.datetime64`
- 'float'
- 'longfloat' : 128-bit floats
- 'complexfloat'
- 'longcomplexfloat' : composed of two 128-bit floats
- 'void' : type `numpy.void`
- 'numpystr' : types `numpy.string_` and `numpy.unicode_`
- 'str' : all other strings

Other keys that can be used to set a group of types at once are:

- 'all' : sets all types
- 'int_kind' : sets 'int'
- 'float_kind' : sets 'float' and 'longfloat'
- 'complex_kind' : sets 'complexfloat' and 'longcomplexfloat'
- 'str_kind' : sets 'str' and 'numpystr'

threshold : int, optional

Total number of array elements which trigger summarization rather than full repr.

edgeitems : int, optional

Number of array items in summary at beginning and end of each dimension.

sign : string, either ‘-‘, ‘+’, or ‘ ‘, optional

Controls printing of the sign of floating-point types. If ‘+’, always print the sign of positive values. If ‘ ‘, always prints a space (whitespace character) in the sign position of positive values. If ‘-‘, omit the sign character of positive values.

floatmode : str, optional

Controls the interpretation of the precision option for floating-point types. Can take the following values:

  • ‘fixed’ : Always print exactly precision fractional digits,

    even if this would print more or fewer digits than necessary to specify the value uniquely.

  • ‘unique : Print the minimum number of fractional digits necessary

    to represent each value uniquely. Different elements may have a different number of digits. The value of the precision option is ignored.

  • ‘maxprec’ : Print at most precision fractional digits, but if

    an element can be uniquely represented with fewer digits only print it with that many.

  • ‘maxprec_equal’ : Print at most precision fractional digits,

    but if every element in the array can be uniquely represented with an equal number of fewer digits, use that many digits for all elements.

legacy : string or False, optional

If set to the string ‘1.13’ enables 1.13 legacy printing mode. This approximates numpy 1.13 print output by including a space in the sign position of floats and different behavior for 0d arrays. If set to False, disables legacy mode. Unrecognized strings will be ignored with a warning for forward compatibility.

New in version 1.14.0.


array_str : str

String representation of the array.



if a callable in formatter does not return a string.


If a formatter is specified for a certain type, the precision keyword is ignored for that type.

This is a very flexible function; array_repr and array_str are using array2string internally so keywords with the same name should work identically in all three functions.


>>> x = np.array([1e-16,1,2,3])
>>> print(np.array2string(x, precision=2, separator=',',
...                       suppress_small=True))
[ 0., 1., 2., 3.]
>>> x  = np.arange(3.)
>>> np.array2string(x, formatter={'float_kind':lambda x: "%.2f" % x})
'[0.00 1.00 2.00]'
>>> x  = np.arange(3)
>>> np.array2string(x, formatter={'int':lambda x: hex(x)})
'[0x0L 0x1L 0x2L]'

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