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Technical articles with clear explanations and examples
Compare and return True if two string arrays are equal in Numpy
To compare and return True if two string arrays are equal, use the numpy.char.equal() method in Python Numpy. The arr1 and arr2 are the two input string arrays of the same shape. Unlike numpy.equal, this comparison is performed by first stripping whitespace characters from the end of the string. This behavior is provided for backward-compatibility with numarrayThe 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 two One-Dimensional arrays of string −arr1 = np.array(['Bella', 'Tom', 'John', 'Kate', 'Amy', 'Brad']) arr2 = np.array(['Cio', 'Tom', 'Cena', ...
Read MoreReturn the numeric string left-filled with zeros in Numpy
To return the numeric string left-filled with zeros, use the numpy.char.zfill() method in Python Numpy. Here, The 1st parameter is the inout arrayThe 2nd parameter is the "width" i.e. the width of string to left-fill elements in arrayThe 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 string −arr = np.array(['Tom', 'John', 'Kate', 'Amy', 'Brad']) Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype) Get the dimensions of the Array −print("Array Dimensions...", arr.ndim)Get the shape of the Array −print("Our ...
Read MoreHow to wait for a goroutine to finish in Golang?
We know that goroutines can be a bit tricky at first, and often we find cases where the main goroutines will exit without giving a chance to the inside goroutines to execute.In order to be able to run the goroutines until the finish, we can either make use of a channel that will act as a blocker or we can use waitGroups that Go's sync package provides us with.Let's first explore a case where we have a single goroutines that we want to finish and then do some other work.Example 1Consider the code shown below.package main import ( "fmt" ...
Read MoreHow 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 ...
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