Found 1204 Articles for Numpy

Mask rows and/or columns of a 2D array that contain masked values along axis 1 in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:41:21

219 Views

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 More

Return the outer product of two masked arrays with different shapes in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:39:26

156 Views

To return the outer product of two masked arrays with different shapes, use the ma.outer() method in Python Numpy. The first parameter is the input vector. Input is flattened if not already 1-dimensional. The second parameter is the second input vector. Input is flattened if not already 1-dimensional.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 More

Compare and return True if a Numpy array is greater than equal to another

AmitDiwan
Updated on 18-Feb-2022 07:37:03

449 Views

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 = ... Read More

Return an array with the elements of a Numpy array right-justified in a string of length width

AmitDiwan
Updated on 18-Feb-2022 07:34:59

93 Views

To return an array with the elements of an array right-justified in a string of length width, use the numpy.char.rjust() method in Python Numpy. The "width" parameter is the length of the resulting strings.The function 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 np# Create a One-Dimensional array of stringarr = 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 ... Read More

Left-justify elements of an array and set the characters to use for padding in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:32:26

128 Views

To left-justify elements of an array and set the characters to use for padding, use the numpy.char.ljust() method in Python Numpy. The "width" parameter is the length of the resulting strings. The "fillchar" parameter is the character to use for padding.The function 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 string −arr = np.array(['Tom', 'John', 'Kate', 'Amy', 'Brad'])Displaying our array −print("Array...", arr)Get the datatype: −print("Array datatype...", ... Read More

Return an array with the elements of an array left-justified in a string of length width in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:30:38

124 Views

To return an array with the elements of an array left-justified in a string of length width, use the numpy.char.ljust() method in Python Numpy. The "width" parameter is the length of the resulting strings. The function 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 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 ... Read More

Compare and return True if two string Numpy arrays are not equal

AmitDiwan
Updated on 18-Feb-2022 07:28:28

313 Views

To compare and return True if two string arrays are not equal, use the numpy.char.not_equal() method in Python Numpy. The arr1 and arr2 are the two input string arrays of the same shape.Unlike numpy.not_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']) arr2 = np.array(['Bella', 'Tom', 'Cena', ... Read More

Unpack elements of a uint8 array into a binary-valued output array in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:26:39

1K+ Views

To unpack elements of a uint8 array into a binary-valued output array, use the numpy.unpackbits() method in Python Numpy. The result is binary-valued (0 or 1).Each element of the input array represents a bit-field that should be unpacked into a binary-valued output array. The shape of the output array is either 1-D (if axis is None) or the same shape as the input array with unpacking done along the axis specified.The axis is the dimension over which bit-unpacking is done. None implies unpacking the flattened array. The count parameter is the number of elements to unpack along axis, provided as ... Read More

Pack the elements of a binary-valued Numpy array into bits in a uint8 array over negative axis

AmitDiwan
Updated on 18-Feb-2022 07:24:27

237 Views

To pack the elements of a binary-valued array into bits in a uint8 array, use the numpy.packbits() method in Python Numpy. The result is padded to full bytes by inserting zero bits at the end. The axis is set using the axis parameter. The axis is the dimension over which bit-packing is done. We have set negative axis.The axis is the dimension over which bit-packing is done. None implies packing the flattened array. The bitorder is the order of the input bits. 'big' will mimic bin(val), [0, 0, 0, 0, 0, 0, 1, 1] ⇒ 3 = 0b00000011, 'little' will ... Read More

Return a list of the words in the string using separator as the delimiter string in Numpy

AmitDiwan
Updated on 18-Feb-2022 07:22:05

77 Views

To return a list of the words in the string using separator as the delimiter string, use the numpy.char.split() method in Python Numpy −The 1st parameter is the input arrayThe 2nd parameter is the separatorIf maxsplit parameter is given, at most maxsplit splits are done. The function split() returns an array of list objects.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 an array −arr = np.array(["Bella-Cio", "Brad-Pitt", "Katie-Perry"])Displaying our array −print("Array...", arr)Get the datatype −print("Array datatype...", arr.dtype) Get the dimensions of the ... Read More

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