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Method argpartition

NumPy Random Generator4 topics

Method choice Method dot Method finfo Method histogram Method iinfo Method max Method mean Method place Method roots Method seed Method uniform Method view Method zeros Method sum Object busdaycalendar Method is_busday Property dtype Method unique Method loadtxt Method vsplit Method fliplr Method setdiff1d Method msort Method argsort Method lexsort Method around Method nanmax Method nanmin Method nanargmax Method nanargmin Method argmax Method argmin Property itemsize Method spacing Method fix Method ceil Method diff Property flat Property real Property base Method flip Method delete Method amax Method amin Method logical_xor Method logical_or Method logical_not Method logical_and Method logaddexp Method logaddexp2 Method logspace Method not_equal Method equal Method greater_equal Method less Method less_equal Method remainder Method mod Method empty Method greater Method isfinite Method busday_count Method repeat Method var Method random_sample Method random Method sign Method std Method absolute Method abs Method sort Method randint Method isreal Method linspace Method gradient Method all Method sample Property T Property imag Method cov Method insert Method log Method log1p Method exp2 Method expm1 Method exp Method arccos Method cos Method arcsin Method sin Method tan Method fromiter Method trim_zeros Method diagflat Method savetxt Method count_nonzero Property size Property shape Method reshape Method resize Method triu Method tril Method eye Method arange Method fill_diagonal Method tile Method save Method transpose Method swapaxes Method meshgrid Property mgrid Method rot90 Method log2 Method radians Method deg2rad Method rad2deg Method degrees Method log10 Method append Method cumprod Property nbytes Method tostring Property data Method modf Method fmod Method tolist Method datetime_as_string Method datetime_data Method array_split Method itemset Method floor Method put_along_axis Method cumsum Method bincount Method put Method putmask Method take Method hypot Method sqrt Method square Method floor_divide Method tri Method signbit Method flatten Method ravel Method roll Method isrealobj Method diag Method diagonal Method quantile Method ones Method iscomplexobj Method iscomplex Method isscalar Method divmod Method isnat Method percentile Method isnan Method divide Method add Method reciprocal Method positive Method subtract Method median Method isneginf Method isposinf Method float_power Method power Method negative Method maximum Method average Method isinf Method multiply Method busday_offset Method identity Method interp Method squeeze Method get_printoptions Method savez_compressed Method savez Method load Method asfarray Method clip Method array Method array_equiv Method array_equal Method frombuffer Method set_string_function Method matmul Method genfromtxt Method fromfunction Method asscalar Method searchsorted Method full_like Method full Method shares_memory Method ptp Method digitize Method argwhere Method geomspace Method zeros_like Method fabs Method flatnonzero Method vstack Method dstack Method fromstring Method tobytes Method expand_dims Method ranf Method arctan Method item Method extract Method compress Method choose Method asarray Method asmatrix Method allclose Method isclose Method any Method corrcoef Method trunc Method prod Method cross Method true_divide Method hsplit Method split Method rint Method ediff1d Method lcm Method gcd Method cbrt Method flipud Property ndim Method array2string Method set_printoptions Method where Method hstack

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NumPy | itemsize property

schedule Aug 12, 2023

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Numpy's itemsize property returns the memory size of the array's data-type in bytes.

Examples


        
        
            
                
                
                    a = np.array([1,2,3], dtype="int64")
a.itemsize
                
            
            8

Here, the contents in the array are irrelevant - only the data-type is important here. We set the datatype of the array as "int64", which means that each item in the array will be 8 bytes (i.e. 64 bits). This is exactly what the output is telling us.

To drive home the concept, consider the following:


        
        
            
                
                
                    a = np.array([1,2,3], dtype="int32")
a.itemsize
                
            
            4

Here, 32-bit integer corresponds to 4 bytes, and so that's what is returned.

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