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The numpy.fromiter() function is used to create an ndarray by using a python iterable object. This method mainly returns a one-dimensional ndarray object. Syntax of numpy.fromiter(): Below we have the required syntax to use this function: Parameters: Let us discuss the parameters of the above function: Note: It is important to specify a count parameter in order to improveContinue Reading

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This function is used to return evenly spaced numbers over a specified interval. Syntax of numpy.linspace(): The required syntax to use this function is as follows: Parameters: The parameters of the above-mentioned function are as follows: Returned Values: This function will return the array within the range specified. This function willContinue Reading

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The numpy.logspace() function in Numpy is used to create an array by using the numbers that are evenly separated on a log scale. Syntax of numpy.logspace(): The syntax to use this function is as follows: Parameters: The parameters of this function are as follows: Returned Values: This function will return the array in theContinue Reading

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The numpy.frombuffer() function of the Numpy library is used to create an array by using the specified buffer. This function interprets a buffer as a 1-dimensional array. Syntax of frombuffer(): Given below is the required syntax that is used for numpy.frombuffer() function: Parameters: Let us discuss the parameters of the above constructor: Let us nowContinue Reading

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The numpy.asarray() function in Numpy is used to convert the input or any existing data into an array. Syntax of numpy.asarray(): Given below is the basic syntax to use this function: Parameters: Let us discuss the parameters mentioned above for the asarray() function: Returned Values: This function will return an array with all the values from the sequenceContinue Reading

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The dot() function is mainly used to calculate the dot product of two vectors. Syntax of numpy.dot(): The syntax required to use this function is as follows: Parameters: Let us discuss the parameters of this function: Returned Values: The dot() function will return the dot product of a and b. If both a and b are scalars or if both are 1-D arraysContinue Reading

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In Numpy, the bitwise_and() function is mainly used to perform the bitwise_and operation. Let us take a look at the truth table of AND operation: If and only if both the bits are 1 only then the output of the AND result of the two bits is 1 otherwise it will be 0. Syntax of bitwise_and():Continue Reading

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In Numpy, the bitwise_or() function is mainly used to perform the bitwise_or operation. Given below is the truth table of OR operation where you will see the OR result of the two bits is 1 if one of the bits is 1 otherwise the result will be 0. Syntax of bitwise_or(): The syntax required to use thisContinue Reading

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Syntax of numpy.invert(): The syntax required to use this function is as follows: Parameters: Let us now take a look at the parameters of this function: Returned Values: This function will return a scalar if x is scalar. Example 1: In the example below, we will illustrate the usage of the invert() function:Continue Reading

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In Numpy, the bitwise_xor() function is mainly used to perform the bitwise XOR operation. Syntax of numpy.bitwise_xor(): The syntax required to use this function is as follows: Parameters: let us now take a look at the parameters of this function: Returned Values: This function will return a scalar if both x1 and x2 are scalars. Example 1:Continue Reading