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Tag Archives: Python numpy-Indexing

Sometimes in Numpy array, we want to apply certain conditions to filter out some values and then either replace or remove them. The conditions can… Read More
Sometimes we need to remove values from the source Numpy array and add them at specific indices in the target array. In NumPy, we have… Read More
Let us see how to access different rows of a multidimensional array in NumPy. Sometimes we need to access different rows of multidimensional NumPy array-like first… Read More
Let’s see how to getting the row numbers of a numpy array that have at least one item is larger than a specified value X.… Read More
Sometimes we need to find out the indices of all null elements in the array. Numpy provides many functions to compute indices of all null… Read More
The elements of a NumPy array are indexed just like normal arrays. The index of the first element will be 0 and the last element… Read More
Accessing a NumPy based array by specific Column index can be achieved by the indexing. Let’s discuss this in detail. NumPy follows standard 0 based… Read More
NumPy (Numerical Python) is a Python library that comprises of multidimensional arrays and numerous functions to perform various mathematical and logical operations on them. NumPy… Read More
NumPy is a general-purpose array-processing package. It provides a high-performance multidimensional array object and tools for working with these arrays. It is the fundamental package… Read More
With the help of np.triu_indices() method, we can get the indices for the upper triangle of an [n, m] array by using np.triu_indices() method. Syntax… Read More
The numpy.where() function returns the indices of elements in an input array where the given condition is satisfied. Syntax :numpy.where(condition[, x, y]) Parameters: condition :… Read More
numpy.nonzero()function is used to Compute the indices of the elements that are non-zero. It returns a tuple of arrays, one for each dimension of arr,… Read More
The numpy.diag_indices() function returns indices in order to access the elements of main diagonal of a array with minimum dimension = 2. Returns indices in… Read More
The method makes changes in the array according the parameters – conditions and value(uses first N-values to put into array as per the mask… Read More
The numpy.compress() function returns selected slices of an array along mentioned axis, that satisfies an axis. Syntax: numpy.compress(condition, array, axis = None, out = None)… Read More