Numpy MCQs with answers Page - 5

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Q. What is the purpose of np.einsum()?

  • (A) To perform summation over specified axes using Einstein notation
  • (B) To compute element-wise exponential functions
  • (C) To calculate the inverse of a matrix
  • (D) To perform element-wise multiplication

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Q. Which function is used to compute both eigenvalues and eigenvectors of a square matrix?

  • (A) np.linalg.svd
  • (B) np.linalg.inv
  • (C) np.linalg.eig
  • (D) np.linalg.cholesky

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Q. What does adding np.newaxis to an array index do?

  • (A) It increases the dimensions of the array
  • (B) It decreases the dimensions of the array
  • (C) It transposes the array
  • (D) It reshapes the array into a flat vector

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Q. Which module within NumPy is dedicated to linear algebra operations?

  • (A) np.linalg
  • (B) np.random
  • (C) np.fft
  • (D) np.core

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Q. What does the np.ma module in NumPy provide?

  • (A) Support for arrays with masked (missing or invalid) data
  • (B) Advanced matrix algebra routines
  • (C) Memory management for large arrays
  • (D) An interface for parallel computing

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Q. Which of the following functions is part of the Fast Fourier Transform (FFT) capabilities in NumPy?

  • (A) np.fft.fft
  • (B) np.fft.ifft
  • (C) np.fft.fftn
  • (D) All of the above

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Q. How do you compute the determinant of a matrix using NumPy?

  • (A) np.linalg.det
  • (B) np.det
  • (C) np.linalg.diag
  • (D) np.matrix.det

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Q. Which function is used to stack arrays vertically?

  • (A) np.vstack()
  • (B) np.hstack()
  • (C) np.stack()
  • (D) np.concatenate()

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Q. Which NumPy function computes the element-wise natural logarithm of an array?

  • (A) np.log10()
  • (B) np.log2()
  • (C) np.log()
  • (D) np.ln()

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Q. What is the primary function of np.histogram()?

  • (A) To calculate a histogram of data
  • (B) To sort the data
  • (C) To compute cumulative sums
  • (D) To filter outliers from data

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