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.argmax(arr)print(...
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 ...
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 Compute rank-based statistics of elem...
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 ...
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 true np.all N/A Evaluate whether all elements are true ...
导入numpy库:在代码中导入numpy库,以便使用其中的函数和方法。 代码语言:txt 复制 import numpy as np 创建数组:使用numpy库的array函数创建一个数组。 代码语言:txt 复制 arr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) 定义部分:确定要查找平均值的数组部分的起始索引和结束索引。
我想找到最接近给定数字的值。一切正常。但问题是,它产生nan两个唯一数字的输出。在这里我提供我的完整数据我的代码和输出:### Find the index of nearest value in a arraydef find_nearest(array, value): array = np.asarray(array) idx = (np.abs(array - value)).argmin() return array[idx] #fo...
phi=(1+np.sqrt(5))/2print("Phi",phi)#2\.Find the index below4million n=np.log(4*10**6*np.sqrt(5)+0.5)/np.log(phi)print(n)#3\.Create an arrayof1-n n=np.arange(1,n)print(n)#4\.Compute Fibonacci numbers fib=(phi**n-(-1/phi)**n)/np.sqrt(5)print("First 9 Fibona...
Find the indexes where the value 7 should be inserted, starting from the right: import numpy as nparr = np.array([6, 7, 8, 9]) x = np.searchsorted(arr, 7, side='right')print(x) Try it Yourself » Example explained: The number 7 should be inserted on index 2 to remain the...
(nums)# find the indices of the second-largest value in each columnindices=np.argsort(nums,axis=0)[-2,:]# get the second-largest value in each column using the indicessecond_largest_values=nums[indices,np.arange(nums.shape[1])]print("\nSecond-largest value in each column:")print(...