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In this article, let's discuss finding the nearest value and the index in an array with Numpy. We will make use of two of the functions provided by the NumPy library to calculate the nearest value and the index in the array. Those two functions are numpy.abs() and numpy.argmin(). Example Input Arra
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BetaThis problem can be solved efficiently using the numpy_indexed library (disclaimer: I am its author); which was created to address problems of this type. npi.indices can be viewed as an n-dimensional generalisation of list.index. It will act on nd-arrays (along a specified axis); and also will look up multiple entries in a vectorized manner as opposed to a single item at a time.
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BetaYou can use the following methods to find the index position of specific values in a NumPy array: Method 1: Find All Index Positions of Value. np. where (x== value) Method 2: Find First Index Position of Value. np. where (x== value)[0][0] Method 3: Find First Index Position of Several Values
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BetaThe return value is an array: [1 2 3] containing the three indexes where 2, 4, 6 would be inserted in the original array to maintain the order. Previous Next ★ +1
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BetaIn this example, the first index value is 0 for both index arrays, and thus the first value of the resultant array is y[0, 0]. The next value is y[2, 1], and the last is y[4, 2]. If the index arrays do not have the same shape, there is an attempt to broadcast them to the same shape. If they cannot be broadcast to the same shape, an exception is ...
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BetaIn this example, we first import the NumPy library and create an array containing some integers. We then specify the element we want to find, which is 20.The np.where() function checks the condition array == element_to_find and returns the indices where this condition is true. By accessing the first element of the returned array with [0][0], we obtain the first index of 20, which in this case ...
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BetaThe returned tuple from np.where() contains two numpy arrays. The first array values tell the row indexes whereas the second array values tell the column indexes of the occurrences of the element inside the 2D array. Let’s make these indexes more readable by showing the (row, column) index tuples for each occurrence.
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BetaNumPy: squeeze() to remove dimensions of size 1 from an array; NumPy: Delete rows/columns from an array with np.delete() NumPy: Round array elements (np.round, np.around, np.rint) NumPy: Views and copies of arrays; NumPy: Read and write CSV files (np.loadtxt, np.genfromtxt, np.savetxt) Check NumPy version: np.version; NumPy: Broadcasting rules ...
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BetaNumPy offers an efficient function that you can use for this problem of finding the index of your desired values. You can simply specify a condition that identifies your desired value and this function returns the indices for the True results of that condition. Here is an example of this function which finds the non-zeros elements in an array:
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BetaInput Array: [12 40 65 78 10 99 30] Nearest value is to be found: 85 Nearest values: 78 Index of nearest value: 3 Approach to Find the nearest value and the index of NumPy Array. Take an array, say, arr[] and an element, say x to which we have to find the nearest value. Call the numpy.abs(d) function, with d as the difference between the ...
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