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Programming Articles
Page 2051 of 2547
How to read a file into a string in Golang?
To read a file into a string, we need to make use of the io/ioutil package that Go's standard library provides us with.Inside the io/ioutil package, there's a function called ReadFile() which is used to open a file and then convert its contents into a slice of bytes, and if for some reason, it isn't able to do so, then it will return an error too.Here is the syntax of the ReadLine() function.func ReadFile(filename string) ([]byte, error)It should be noted that if the above function has made a successful call, then it will return err == nil, not err == ...
Read MoreHow to parse JSON files in Golang?
Suppose we want to read a JSON file in Go. By reading, we mean that we want to convert the file data into a struct in Go.Consider the JSON file shown below that we will use to read and then convert the data into the structure.{ "users": [ { "name": "Mukul Latiyan", "social": { "facebook": "https://facebook.com/immukul", "twitter": "https://twitter.com/immukul", "linkedin": "https://linkedin.com/immukul" } }, ...
Read MoreReturn the data of a masked array as an ndarray
To return the data of a masked array as an ndarray, use the ma.getdata() method in Python Numpy. Returns the data of a (if any) as an ndarray if a is a MaskedArray, else return a as a ndarray or subclass if not.The subok parameter suggest whether to force the output to be a pure ndarray (False) or to return a subclass of ndarray if appropriate (True, default).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 ...
Read MoreReturn the mask of a masked array when mask is equal to nomask
To return the mask of a masked array, 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 or not.StepsAt first, import the required ...
Read MoreDetermine whether input is an instance of a Numpy masked array
To determine whether input is an instance of masked array, use the ma.isMaskedArray() method in Python Numpy. This function returns True if x is an instance of MaskedArray and returns False otherwise. Any object is accepted as input.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 ...
Read MoreDetermine whether input has masked values
To determine whether input has masked values, use the ma.is_masked() method in Python Numpy. Accepts any object as input, but always returns False unless the input is a MaskedArray containing masked values. Returns True if the array is a MaskedArray with masked values, False otherwise.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 ...
Read MoreRemove axes of length one from an array over specific axis in Numpy
Squeeze the Array shape using the numpy.squeeze() method. This removes axes of length one from an array over specific axis. The axis is set using the "axis" parameter.The function returns the input array, but with all or a subset of the dimensions of length 1 removed. This is always a itself or a view into the input array. If all axes are squeezed, the result is a 0d array and not a scalar.The axis selects a subset of the entries of length one in the shape. If an axis is selected with shape entry greater than one, an error is ...
Read MoreMask rows and/or columns of a 2D array that contain masked values along axis 0 in Numpy
To mask rows and/or columns of a 2D array that contain masked values, use the np.ma.mask_rowcols() method in Numpy. The function returns a modified version of the input array, masked depending on the value of the axis parameter.Mask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis parameter −If axis is None, rows and columns are masked.If axis is 0, only rows are masked.If axis is 1 or -1, only columns are masked.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with ...
Read MoreMask rows and/or columns of a 2D array that contain masked values along axis 1 in Numpy
To mask rows and/or columns of a 2D array that contain masked values, use the np.ma.mask_rowcols() method in Numpy. The function returns a modified version of the input array, masked depending on the value of the axis parameterMask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis parameter −If axis is None, rows and columns are masked.If axis is 0, only rows are masked.If axis is 1 or -1, only columns are masked.StepsAt first, import the required library −import numpy as np import numpy.ma as maCreate an array with ...
Read MoreCompare and return True if a Numpy array is greater than equal to another
To compare and return True if an array is greater than equal to another, use the numpy.char.greater_equal() method in Python Numpy. The arr1 and arr2 are the two input string arrays of the same shape.Unlike numpy.greater_equal, this comparison is performed by first stripping whitespace characters from the end of the string. This behavior is provided for backward-compatibility with numarray.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 two One-Dimensional arrays of string −arr1 = np.array(['Bella', 'Tom', 'John', 'Kate', 'Amy', 'Brad', 'aaa']) arr2 = ...
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