importnumpyasnp arr=np.array([5,2,8,1,9,3,7])min_index=np.argmin(arr)print("numpyarray.com: Index of minimum value:",min_index) Python Copy Output: np.argmin()返回数组中最小值的索引。 5.2 使用numpy.argmax() importnumpyasnp arr=np.array([5,2,8,1,9,3,7])max_index=np.ar...
# import libraryimportnumpyasnp# create a numpy 1d-arrayarray=np.array([1,2,3,0,-1,-2])# find index of max element# in an arraymax_ele_index=np.argmax(array)# find max element in an arraymax_ele=array[max_ele_index]# find index of min element# in an arraymin_ele_ind...
np.var np.nanvar Compute variance np.min np.nanmin Find minimum value np.max np.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile...
np.var np.nanvar Compute variance np.minnp.nanmin Find minimum value np.maxnp.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile C...
Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of elements np.any N/A Evaluate whether any elements are ...
np.min np.nanmin Find minimum value np.max np.nanmax Find maximum value np.argmin np.nanargmin Find index of minimum value np.argmax np.nanargmax Find index of maximum value np.median np.nanmedian Compute median of elements np.percentile np.nanpercentile Compute rank-based statistics of ...
numpy.searchsorted(a, v[, side='left', sorter=None]) Find indices where elements should be inserted to maintain order. a:一维输入数组。当sorter参数为None的时候,a必须为升序数组;否则,sorter不能为空,存放a中元素的index,用于反映a数组的升序排列方式。v:插入a数组的值,可以为单个元素,list或者ndarra...
zeros<->zeroseye<->eyeones<->onesmean<->meanwhere<->findsort<->sortsum<->sum其他数学运算:sin,cos,arcsin,arccos,log等 此外,可以通过help(dir(numpy))查看numpy包中的函数: ['ALLOW_THREADS', 'AxisError', 'BUFSIZE', 'CLIP', 'ComplexWarning', 'DataSource', 'ERR_CALL', 'ERR_DEFAULT', ...
13. Create a 10x10 array with random values and find the minimum and maximum values >>Z = np.random.random((10,10)) Zmin, Zmax = Z.min(), Z.max() print(Zmin, Zmax) 14. Create a random vector of size 30 and find the mean value ...
You can specify on which axis you want the aggregation function to be computed. For example, you can find the minimum value within each column by specifyingaxis=0. >>> a.min(axis=0) array([0.12697628, 0.05093587, 0.26590556, 0.5510652 ]) ...