importnumpyasnpdefprocess_array(arr):ifarr.size==0:print("Input array from numpyarray.com is empty")returnnp.array([])returnarr*2empty_input=np.array([])result=process_array(empty_input)print("Result:",result) Python Copy Output: 在函数中处理输入数组时,检查数组是否为空可以避免后续操作中...
In [1]: import numpy as np In [2]: array = np.random.randint(1, 100, 10000).astype(object) ...: array[[1, 2, 6, 83, 102, 545]] = np.nan ...: array[[3, 8, 70]] = None In [3]: %timeit array != array 139 µs ± 46.6 µs per loop (mean ± std. dev. o...
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.zeros(nyears) y_highs = np.zeros(nyears) y_lows = np.zeros(nyears) # Compute stats for year in...
In [40]: a = np.array([[2,2], [2,3]]) In [41]: a.flatten() Out[41]: array([2, 2, 2, 3]) In [43]: a.reshape(-1) Out[43]: array([2, 2, 2, 3]) 但是像这种不规则维度的多维数组就不能转换成功了,还是本身 a = np.array([[[2,3]], [2,3]]) 转换成二维表示的...
numpy.argsort(a[, axis=-1, kind='quicksort', order=None]) Returns the indices that would sort an array. 参考 1.NumPy中文网 2.Numpy实践 二、Pandas 1.数据结构:Series、DataFrame 区别 - series,只是一个一维数据结构,它由index和value组成。 - dataframe,是一个二维结构,除了拥有index和value之外,...
Remove Nan Values Using theisfinite()Method in NumPy As the name suggests, theisfinite()function is a boolean function that checks whether an element is finite or not. It can also check for finite values in an array and returns a boolean array for the same. The boolean array will store...
[5, 95]) array([4.6 , 7.255]) # 把iris_data数据集中的20个随机位置修改为np.nan值。
# Random integersarray = np.random.randint(20, size=12)arrayarray([ 0, 1, 8, 19, 16, 18, 10, 11, 2, 13, 14, 3])# Divide by 2 and check if remainder is 1cond = np.mod(array, 2)==1condarray([False, True, False, True, False, False, False, True, False, ...
a[15,5, :] = np.array([0.5,8.5,0]) Goal: 我想从a中提取非None元素。目前,由于我使用的是基本的for loop,我的以下代码非常耗时且效率很低: bt = time.time() for ci in range(c): if any(ci == value for value in [2, 5]): ...
array([ 3, 5, 7, 9, 11]) 通过上面的两个案例可以看出,在不写for循环的情况下,ndarray数组就可以非常方便的完成数学计算。在编写矢量或者矩阵的程序时,可以像编写普通数值一样,使得代码极其简洁。 另外,ndarray数组还提供了广播机制,它会按一定规则自动对数组的维度进行扩展以完成计算。如下面例子所示,1维数组...