Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Programming Articles
Page 2049 of 2547
How to concatenate two slices in Golang?
Whenever we talk about appending elements to a slice, we know that we need to use the append() function that takes a slice as the first argument and the values that we want to append as the next argument.The syntax looks something like this.sl = append(sl, 1)Instead of appending a single number to the slice "sl", we can append multiple values in the same command as well.Consider the snippet shown below.sl = append(sl, 1, 2, 3, 4)The above code will work fine in Go.When it comes to appending a slice to another slice, we need to use the variadic function ...
Read MoreSorting in Golang with sort Package
The standard library of Golang provides a package that we can use if we want to sort arrays, slices, or even custom types. In this article, we will discover three main functions that we can use if we want to sort a slice in Golang. We will also see how we can create a custom sort function and custom comparator.Let's first check how we can sort a slice of integer, float64 and string values.ExampleConsider the code shown below.package main import ( "fmt" "sort" ) func main() { integerSlice := []int{3, 2, 14, 9, 11} sort.Ints(integerSlice) ...
Read MoreHow to use iota in Golang?
Iota in Go is used to represent constant increasing sequences. When repeated in a constant, its value gets incremented after each specification. In this article, we will explore the different ways in which we can use iota in Go.Let's first consider a very basic example, where we will declare multiple constants and use iota.Example 1Consider the code shown belowpackage main import ( "fmt" ) const ( first = iota second = iota third = iota ) func main() { fmt.Println(first, second, third) }OutputIf we run the command go run main.go, then we will get the ...
Read MoreAnonymous goroutines in Golang
In order to be able to understand the anonymous goroutines, we must be aware of the existence of anonymous functions and goroutines. We will first explore the anonymous functions that are the real reason behind the motivation of anonymous goroutines and then we will learn a little about what goroutines are, before finally checking a few examples of anonymous goroutines.Anonymous functionsIn Golang, anonymous functions are those functions that don't have any name. Simply put, anonymous functions don't use any variables as a name when they are declared.We know that we declare a function with a similar syntax as shown below.func ...
Read MoreReturn element-wise title cased version of string or Unicode in Numpy
To return element-wise title cased version of string or unicode, use the numpy.char.title() method in Python Numpy. Title case words start with uppercase characters, all remaining cased characters are lowercase.The function title() returns an output array of str or unicode, depending on input type. The numpy.char module provides a set of vectorized string operations for arrays of type numpy.str_ or numpy.bytes_.StepsAt first, import the required library −import numpy as npCreate a One-Dimensional array of strings −arr = np.array(['kATIE', 'jOHN', 'Kate', 'AmY', 'brADley']) Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype) Get the dimensions of the Array −print("Array Dimensions...", ...
Read MoreGet the itemsize of the masked array in Numpy
To get the itemsize of the Masked Array, use the ma.MaskedArray.itemsize attribute in 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 maCreate a numpy array using the numpy.array() method −arr = np.array([[35, 85], [67, 33]]) print("Array...", arr) print("Array type...", arr.dtype) print("Array itemsize...", arr.itemsize)Get the dimensions of ...
Read MoreGet the information about the memory layout of the masked array in Numpy
To get the information about the memory layout of the masked array, use the ma.MaskedArray.flags in Numpy. Masked arrays are arrays that may have missing or invalid entries. The numpy.ma module provides a nearly work-alike replacement for numpy that supports data arrays with masks.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 ...
Read MoreReturn the variance of the masked array elements along column axis in Numpy
To return the variance of the masked array elements, use the ma.MaskedArray.var() in Numpy. The axis is set using the axis parameter. The axis is set to 0, for column axis.Returns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the specified axis.The “axis” parameter is the axis or axes along which the variance is computed. The default is to compute the variance of the flattened array. If this is a tuple of ints, a variance is performed over multiple axes, instead of ...
Read MoreReturn the variance of the masked array elements along row axis
To return the variance of the masked array elements, use the ma.MaskedArray.var() in Numpy. The axis is set using the axis parameter. The axis is set to 1, for row axisReturns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the specified axis.The “axis” parameter is the axis or axes along which the variance is computed. The default is to compute the variance of the flattened array. If this is a tuple of ints, a variance is performed over multiple axes, instead of ...
Read MoreCompare and return True if an array is greater than another array in Numpy
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