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The partition() function is used to split up the input array accordingly as per the given arguments. Syntax of numpy.partition(): The syntax required to use this method is as follows: Parameters: let us now take a look at the parameters of this function: Returned Values: This Function will return an Array of the same typeContinue Reading

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The transpose() function in the numpy library is mainly used to reverse or permute the axes of an array and then it will return the modified array. Syntax of numpy.transpose(): The syntax required to use this function is as follows: Parameters: Let us take a look at the parameters of this function: Returned Values: The transpose() functionContinue Reading

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In this tutorial, we will cover the concept of array() function in the NumPy library. The array() function in the NumPy library is mainly used to create an array. Just like the Numpy arange() function. Syntax of numpy.array(): The syntax required to use this method is as follows: Parameters: Let us now take a look atContinue Reading

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In this tutorial, we will cover the concatenate() function of the NumPy library. The concatenate() function is mainly used in order to combine two or more NumPy arrays together. ence we can say that the concatenate() function can be used to join a sequence of arrays along an existing axis. Syntax of numpy.concatenate(): The syntax required toContinue Reading

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In this tutorial, we will cover the numpy.append() function of the NumPy library. The “append” word simply means to add something to the existing data at the end or at the last. Syntax of numpy.append(): The syntax required to use this function is as follows: Parameters: Let us take a look at the parameters of this function:Continue Reading

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In this tutorial, we will cover the reshape() function of the NumPy library. The word “reshape” simply indicates changing the shape and that is what this function is used for Syntax of reshape(): The syntax required to use this function is as follows: Parameters: Let us take a look at the parameters ofContinue Reading

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In this tutorial, we will cover numpy.arange() function of the Numpy library which is used for array creation. The NumPy arange() function is one of the array creation routines that is usually based on numerical ranges. This method basically creates an instance of ndarray with evenly spaced values and returns the reference to it. Syntax of numpy.arange() Below we haveContinue Reading

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In this tutorial, we will cover the concept of Multiplication of two Matrix in the NumPy library. Also, as the NumPy library is mainly used for manipulation and array-processing, so this is a very important concept. In NumPy, the Multiplication of matrix is basically an operation where we take two matrices as input and multiply rows ofContinue Reading

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In this tutorial, we will learn how to iterate over any given array to one by one access all the available elements in the array (array iteration) in the NumPy library. The numpy.nditer is an iterator object provided by the Numpy library. Example 1 Let us take a look at an exampleContinue Reading

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In this tutorial, we will cover the concept of copy and view, for ndarray in the NumPy library. In Numpy, using the copy() and view() functions, we can create a new copy of any existing array or create a new view for the array. Let us take a look at what is the majorContinue Reading