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To compare and return True if an array is greater than another array, use the numpy.char.greater() method in Python Numpy.NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.StepsAt first, import the required library −import numpy as npCreate two One-Dimensional arrays of string −arr1 = np.array(['Bella', 'Tom', 'John', 'Kate', 'Amy', 'Brad', 'aaa']) arr2 = np.array(['Cio', 'Tom', 'Cena', 'Kate', 'Adams', 'brad', 'aa'])Display the arrays −print("Array 1...", arr1) print("Array 2...", arr2)Get the type of the arrays −print("Our ... Read More

To compute the bit-wise OR of two 1D arrays element-wise, use the numpy.bitwise_or() method in Python Numpy. Computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator |.The 1st and 2nd parameter are the arrays, only integer and boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.The where parameter is the condition broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original ... Read More

To return the underlying data, as a view of the masked array, use the ma.MaskedArray.data in Python Numpy.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreating a 4x4 array with int elements using the numpy.arange() method −arr = np.arange(16).reshape((4, 4)) print("Array...", arr) print("Array type...", arr.dtype)Get the dimensions ... Read More

To return the mask of a masked array, use the ma.getmask() method in Python Numpy. Returns the mask of a as an ndarray if a is a MaskedArray and the mask is not nomask, else return nomask. To guarantee a full array of booleans of the same shape as a, use getmaskarray.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid or not.StepsAt ... Read More

To count the number of masked elements along axis 1, use the ma.MaskedArray.count_masked() method. The axis is set using the "axis" parameter. The method returns the total number of masked elements (axis=None) or the number of masked elements along each slice of the given axis.The axis parameter is the axis along which to count. If None (default), a flattened version of the array is used.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreating a 4x4 array with int elements using the numpy.arange() method −arr = np.arange(16).reshape((4, 4)) print("Array...", arr) print("Array type...", arr.dtype)Get the dimensions of ... Read More

To compute the bit-wise OR of two arrays element-wise, use the numpy.bitwise_or() method in Python Numpy. Computes the bit-wise OR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator |.The 1st and 2nd parameter are the arrays, only integer and boolean types are handled. If x1.shape != x2.shape, they must be broadcastable to a common shape.The where parameter is the condition broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. ... Read More

To return the mask of a masked array, or full boolean array of False, use the ma.getmaskarray() method in Python Numpy. Returns the mask of arr as an ndarray if arr is a MaskedArray and the mask is not nomask, else return a full boolean array of False of the same shape as arr.A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of the associated array whether the value is valid ... Read More

The reflect package in Go provides a very important function called DeepEqual() which can be used to compare composite types. The DeepEqual() function is used when we want to check if two data types are "deeply equal".Comparing slicesExample 1Consider the code shown belowpackage main import (    "fmt"    "reflect" ) func main() {    sl := []int{1, 2, 3}    sl1 := []int{1, 2, 3}    fmt.Println(reflect.DeepEqual(sl, sl1)) }OutputIf we run the command go run main.go on the above code, then we will get the following output in the terminal.trueComparing mapsExample 2Consider the code shown below.package main import ( ... Read More

We know that substrings are a contiguous sequence of characters in a string, and in order to check whether a string contains a substring, we have two options available.The first approach is to use a built-in function called Contains() and the second approach is to make use a self-written logic for the same.The syntax for the Contains() function of the strings package is shown below.func Contains(s, substr string) boolIn the above syntax, there are two parameters inside the function Contains(). The first parameter is the string in which we are trying to find the pattern, and the second is the ... Read More

We know that maps in Go contain key-value pairs. There are often instances where we would want to know that a certain key exists in a map or not, in such cases, we have two options available.The first approach is very naive, as in this approach, we basically iterate over the map with the help of the range clause and then compare each key to the key that we want to check if is available or not.And the second approach is a bit better, as we make use of the if statement with a bit of syntactic sugar.Let's first check ... Read More