Introduction to Numpy - Array Inspection

Program 1

Array Inspection

Python 3.11 Ready

import numpy as np

''' Create a NumPy array '''
arr = np.array([1, 2, 3, 4, 5, 8, 9, 10, 14, 7])

''' Inspect the shape of the array '''
print("\nShape of array:", arr.shape)

''' Inspect the size of the array (total number of elements) '''
print("\nSize of array:", arr.size)

''' Inspect the number of dimensions of the array '''
print("\nNumber of dimensions:", arr.ndim)

''' Inspect the data type of the array '''
print("\nData type of array:", arr.dtype)

''' Inspect the length of the array '''
print("\nLength of array:", len(arr))

''' Inspect if all elements are non-zero '''
print("\nAre all elements non-zero?:", np.all(arr))

''' Inspect if any element is non-zero '''
print("\nIs any element non-zero?:", np.any(arr))

''' Inspect the minimum value in the array '''
print("\nMinimum value:", np.min(arr))

''' Inspect the maximum value in the array '''
print("\nMaximum value:", np.max(arr))

''' Inspect the sum of all elements in the array '''
print("\nSum of elements:", np.sum(arr))

''' Inspect the mean of the array elements '''
print("\nMean of elements:", np.mean(arr))

''' Inspect the standard deviation of the array '''
print("\nStandard deviation of elements:", np.std(arr))

''' Inspect the variance of the array '''
print("\nVariance of elements:", np.var(arr))

''' Inspect the cumulative sum of array elements '''
print("\nCumulative sum:", np.cumsum(arr))

''' Inspect the cumulative product of array elements '''
print("\nCumulative product:", np.cumprod(arr))

''' Inspect the indices of the minimum values '''
print("\nIndex of minimum value:", np.argmin(arr))

''' Inspect the indices of the maximum values '''
print("\nIndex of maximum value:", np.argmax(arr))

''' Inspect sorted array '''
print("\nSorted array:", np.sort(arr))

''' Inspect if the array is sorted '''
print("\nIs array sorted?:", np.all(np.diff(arr) >= 0))

''' Inspect the unique elements in the array '''
print("\nUnique elements:", np.unique(arr))

''' Inspect the number of occurrences of each element '''
(unique, counts) = np.unique(arr, return_counts=True)
print("\nOccurrences of elements:", dict(zip(unique, counts)))

''' Inspect the square root of array elements '''
print("\nSquare root of array elements:", np.sqrt(arr))

''' Inspect the logarithm of array elements '''
print("\nNatural log of array elements:", np.log(arr))

''' Inspect the exponential of array elements '''
print("\nExponential of array elements:", np.exp(arr))

''' Inspect the copy behavior of the array '''
arr_copy = np.copy(arr)
print("\nCopied array:", arr_copy)

''' Inspect array reshaping '''
reshaped_arr = arr.reshape(1, -1)
print("\nReshaped array:\n", reshaped_arr)

''' Inspect repeating of array elements '''
repeated_arr = np.repeat(arr, 3)
print("\nRepeated array:", repeated_arr)

''' Inspect where specific conditions are met in the array '''
condition_arr = np.where(arr > 2)
print("\nIndices where condition is met:", condition_arr)

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Mathematical Problem Formulation

Inspect 1D array

Program 2

Array Inspection

Python 3.11 Ready

import numpy as np

''' Create a 2D NumPy array '''
arr_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

''' Inspect the shape of the 2D array '''
print("\nShape of 2D array:", arr_2d.shape)

''' Inspect the number of rows and columns '''
rows, cols = arr_2d.shape
print("\nNumber of rows:", rows)
print("\nNumber of columns:", cols)

''' Inspect the size (total number of elements) of the 2D array '''
print("\nSize of 2D array:", arr_2d.size)

''' Inspect the number of dimensions of the 2D array '''
print("\nNumber of dimensions:", arr_2d.ndim)

''' Inspect the data type of the 2D array '''
print("\nData type of 2D array:", arr_2d.dtype)

''' Inspect the transpose of the 2D array '''
print("\nTranspose of 2D array:\n", arr_2d.T)

''' Inspect the diagonal elements of the 2D array '''
print("\nDiagonal elements:", np.diag(arr_2d))

''' Inspect the sum of all elements in the 2D array '''
print("\nSum of all elements:", np.sum(arr_2d))

''' Inspect the sum along rows (axis 1) '''
print("\nSum along rows:", np.sum(arr_2d, axis=1))

''' Inspect the sum along columns (axis 0) '''
print("\nSum along columns:", np.sum(arr_2d, axis=0))

''' Inspect the mean of all elements in the 2D array '''
print("\nMean of all elements:", np.mean(arr_2d))

''' Inspect the mean along rows '''
print("\nMean along rows:", np.mean(arr_2d, axis=1))

''' Inspect the mean along columns '''
print("\nMean along columns:", np.mean(arr_2d, axis=0))

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Mathematical Problem Formulation

Inspect 2D Array

Program 3

Array Inspection

Python 3.11 Ready

import numpy as np

''' Create a 2D NumPy array '''
arr_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

''' Inspect the maximum value in the 2D array '''
print("\nMaximum value:", np.max(arr_2d))

''' Inspect the minimum value in the 2D array '''
print("\nMinimum value:", np.min(arr_2d))

''' Inspect the index of the maximum value in the 2D array '''
print("\nIndex of maximum value:", np.unravel_index(np.argmax(arr_2d), arr_2d.shape))

''' Inspect the index of the minimum value in the 2D array '''
print("\nIndex of minimum value:", np.unravel_index(np.argmin(arr_2d), arr_2d.shape))

''' Inspect the standard deviation of the 2D array '''
print("\nStandard deviation of all elements:", np.std(arr_2d))

''' Inspect the variance of the 2D array '''
print("\nVariance of all elements:", np.var(arr_2d))

''' Inspect the cumulative sum along rows '''
print("\nCumulative sum along rows:\n", np.cumsum(arr_2d, axis=1))

''' Inspect the cumulative sum along columns '''
print("\nCumulative sum along columns:\n", np.cumsum(arr_2d, axis=0))

''' Inspect reshaping the 2D array into a 1D array '''
reshaped_arr = arr_2d.reshape(-1)
print("\nReshaped to 1D array:", reshaped_arr)

''' Inspect flattening the 2D array into a 1D array '''
flattened_arr = arr_2d.flatten()
print("\nFlattened array:", flattened_arr)

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Mathematical Problem Formulation

Inspect 2D Array

Program 4

Array Inspection

Python 3.11 Ready

import numpy as np

''' Create a 2D NumPy array '''
arr_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

''' Inspect converting a 1D array back into a 2D array '''
arr_1d = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
reshaped_back = arr_1d.reshape(3, 3)
print("\nReshaped back to 2D array:\n", reshaped_back)

''' Inspect slicing a submatrix from the 2D array '''
submatrix = arr_2d[0:2, 1:3]
print("\nSliced submatrix:\n", submatrix)

''' Inspect accessing a specific row in the 2D array '''
row_1 = arr_2d[1, :]
print("\nRow 1 of the 2D array:", row_1)

''' Inspect accessing a specific column in the 2D array '''
col_2 = arr_2d[:, 2]
print("\nColumn 2 of the 2D array:", col_2)

''' Inspect stacking two 2D arrays vertically '''
arr_2d_2 = np.array([[10, 11, 12], [13, 14, 15], [16, 17, 18]])
stacked_vertically = np.vstack((arr_2d, arr_2d_2))
print("\nVertically stacked arrays:\n", stacked_vertically)

''' Inspect stacking two 2D arrays horizontally '''
stacked_horizontally = np.hstack((arr_2d, arr_2d_2))
print("\nHorizontally stacked arrays:\n", stacked_horizontally)

''' Inspect splitting the 2D array into sub-arrays along rows '''
split_row = np.split(arr_2d, 3, axis=0)
print("\nRow-wise split arrays:", split_row)

''' Inspect splitting the 2D array into sub-arrays along columns '''
split_col = np.split(arr_2d, 3, axis=1)
print("\nColumn-wise split arrays:", split_col)

''' Inspect repeating elements of the 2D array '''
repeated_arr = np.repeat(arr_2d, 2, axis=0)
print("\nRepeated array along rows:\n", repeated_arr)

''' Inspect tiling the 2D array '''
tiled_arr = np.tile(arr_2d, (2, 1))
print("\nTiled array:\n", tiled_arr)

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Program 5

Array Inspection

Python 3.11 Ready

import numpy as np

''' Create a 2D NumPy array '''
arr_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

''' Inspect converting the 2D array into a 3D array '''
arr_3d = arr_2d.reshape(3, 3, 1)
print("\nReshaped to 3D array:\n", arr_3d)

''' Inspect generating an identity matrix '''
identity_matrix = np.eye(3)
print("\nIdentity matrix:\n", identity_matrix)

''' Inspect where a condition is true in the 2D array '''
condition_indices = np.where(arr_2d > 5)
print("\nIndices where elements are greater than 5:", condition_indices)

''' Inspect masking elements based on a condition '''
masked_array = np.ma.masked_where(arr_2d > 5, arr_2d)
print("\nMasked array:\n", masked_array)

''' Inspect sorting each row of the 2D array '''
sorted_rows = np.sort(arr_2d, axis=1)
print("\nRows sorted individually:\n", sorted_rows)

''' Inspect sorting each column of the 2D array '''
sorted_cols = np.sort(arr_2d, axis=0)
print("\nColumns sorted individually:\n", sorted_cols)

''' Inspect finding the unique elements of the 2D array '''
unique_elements = np.unique(arr_2d)
print("\nUnique elements in the 2D array:", unique_elements)

''' Inspect counting the occurrences of each unique element in the 2D array '''
(unique_vals, counts) = np.unique(arr_2d, return_counts=True)
print("\nOccurrences of unique elements:", dict(zip(unique_vals, counts)))

''' Inspect changing the data type of the 2D array '''
arr_float = arr_2d.astype(float)
print("\n2D array with float data type:\n", arr_float)

''' Inspect clipping (limiting) the values of the 2D array '''
clipped_arr = np.clip(arr_2d, 3, 7)
print("\nClipped 2D array (values between 3 and 7):\n", clipped_arr)

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Mathematical Problem Formulation

Inspect 2D Array

Program 6

Array Inspection

Python 3.11 Ready

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Mathematical Problem Formulation

Complex Array

Ch. 7.3 Array Inspection

Array Inspection

Mathematical Problem Formulation

Array Inspection

Mathematical Problem Formulation

Array Inspection

Mathematical Problem Formulation

Array Inspection

Array Inspection

Mathematical Problem Formulation

Array Inspection

Mathematical Problem Formulation