print(np.max(my_array, axis = 0)) # Get max of array columns # [4 5 6]print(np.min(my_array, axis = 0)) # Get min of array columns # [1 2 3]As you can see, the previous Python codes have returned the maximum and minimum of our NumPy array by column....
Example 1: minimum() With 2-D Array importnumpyasnp# create two 2-D arraysarray1 = np.array([[1,2,3], [4,5,6]]) array2 = np.array([[2,4,1], [5,3,2]]) # find the element-wise minimum of array1 and array2result = np.minimum(array1, array2) print(result) Run Code...
Reference NumPy nanmin Official Documentation Tanvi Bugdani Articles: 63 PreviousPostNumPy nanmax - Maximum of an array along an axis ignoring any NaNs NextPostNumpy Gradient: Returning the Gradient of N-dimensional Array
numpy.amin(a[, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue, where=np._NoValue])Return the minimum of an array or minimum along an axis. 【例】计算最小值 importnumpyasnpx=np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]])#计算整个矩阵中...
numpy.minimum(x1,x2,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature,extobj])= <ufunc 'minimum'> Element-wise minimum of array elements. Compare two arrays and returns a new array containing the element-wise minima. If one of the elements being ...
Return the minimum of an array or minimum along an axis. max(a, axis]) Return the maximum of an array or maximum along an axis. median(a, axis)(中位数) Compute the median along the specified axis. mean(a, axis, dtype)(均值) Compute the arithmetic mean along the specified axis...
ma.array(avgs, mask = avgs == 0) lows = np.ma.array(lows, mask = lows == 0) highs = np.ma.array(highs, mask = highs == 0) # Get years years = data[:,0]/10000 # Initialize annual stats arrays y_range = np.arange(1901, 2014) nyears = len(y_range) y_avgs = np....
1. >>> import numpy as np2. >>> a = np.array([1, 2, 3, 4, 5])3. >>> b = np.array([True, False, True, False, True])4. >>> a[b]5. array([1, 3, 5])6. >>> b = np.array([False, True, False, True, False])7. >>> a[b]8. array([2, 4])9. >>> ...
arr_1#结果:>>> array([1, 2, 3, 4])#创建二维数组arr_2 = np.array([[1,2,3],[4,5,6]]) arr_2#结果>>> array([[1, 2, 3], [4, 5, 6]])#注意:numpy默认ndarray的所有元素的类型是相同的 如果传进来的列表中包含不同的类型,则统一为同一类型,优先级:str>float>int ...
Maximum value of the above flattened array: 3 Minimum value of the above flattened array: 0 Explanation: In the above exercise – a = np.arange(4).reshape((2,2)): This line creates a 2D array of shape (2, 2) using the np.arange function and then reshape it to the desired shape ...