arr=np.array([1,2,3,2,1])max_index=np.argmax(arr)print(max_index)# 输出 2 Python Copy Output: 示例代码 2:指定轴 importnumpyasnp arr=np.array([[1,2,3],[4,5,6],[7,8,9]])max_indices=np.argmax(arr,axis=0)print(max_indices)# 输出 [2, 2, 2] Python Copy Output: 2. ...
all,any,apply_along_axis,argmax,argmin,argsort,average,bincount,ceil,clip,conj,corrcoef,cov,cross,cumprod,cumsum,diff,dot,floor,inner,invert,lexsort,max,maximum,mean,median,min,minimum,nonzero,outer,prod,re,round,sort,std,sum,trace,transpose,var,vdot,vectorize,where 索引、切片和迭代 一维数组可...
代码如下: 方法一： //最小值 Array.prototype.min = function() { var min = this[0]; var le...
34在 NumPy 数组中找到最大值的索引 import numpy as np the_array = np.array([11, 22, 53, 14, 15]) max_index_col = np.argmax(the_array, axis=0) print(max_index_col) Output: 2 35按降序对 NumPy 数组进行排序 按降序对 Numpy 进行排序 import numpy as np the_array = np.array([...
np.max(arr) --- 6 14、unique 返回一个所有唯一元素排序的数组。 return_index:如果为True,返回数组的索引。 return_inverse:如果为True,返回唯一数组的下标。 return_counts:如果为True,返回数组中每个唯一元素出现的次数。 axis:要操作的轴。默认情况...
array([1, 8, 2, 0], dtype=int64)np.sort(x[index_val])array([10, 12, 12, 16])3. clip()Clip() 用于将值保留在间隔的数组中。有时，需要将值保持在上限和下限之间。因此，可以使用NumPy的clip()函数。给定一个间隔，该间隔以外的值都将被裁剪到间隔边缘。x = np.array([3, 17, 14, 23,...
msft = quandl.get('WIKI/MSFT') msft['Daily Pct. Change'] = (msft['Adj. Close'] - msft['Adj. Open']) / msft['Adj. Open'] data = [go.Scatter(x=msft.index, y=msft['Adj. Close'])] plot(data) 我们从前面的代码中获得以下图表,如下图所示: ...
def __init__(self,layer_index, is_output, input_dim, output_dim, activation): self.layer_index = layer_index# zero indicates input layer self.is_output =is_output # true indicates output layer, false otherwise self.input_dim =input_dim self.output_dim =output_dim self.activation =activa...
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.anyN/A Evaluate whetheranyelements are true np.allN/A Evaluate whetherallelements are true ...
(connected=True)from datetime import datetimeimport pandas_datareader.data as webimport quandlmsft = quandl.get('WIKI/MSFT')msft['Daily Pct. Change'] = (msft['Adj. Close'] - msft['Adj. Open']) / msft['Adj. Open']data = [go.Scatter(x=msft.index, y=msft['Adj. Close'])]plot(...