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## Freshers / Beginner level questions & answers

### Ques 1. What is NumPy?

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with mathematical functions to operate on these arrays.

### Ques 2. How to install NumPy?

You can install NumPy using the command 'pip install numpy'.

### Ques 3. Create a NumPy array from a Python list.

import numpy as npnmy_list = [1, 2, 3]narr = np.array(my_list)

### Ques 4. How to find the dimension of a NumPy array?

You can use the attribute 'ndim'. For example, if 'arr' is your array, use 'arr.ndim'.

### Ques 5. What is the difference between 'np.zeros()' and 'np.ones()' in NumPy?

'np.zeros()' creates an array filled with zeros, while 'np.ones()' creates an array filled with ones.

### Ques 6. How to access elements from a 2D NumPy array?

You can use indices. For example, 'arr[1, 2]' accesses the element in the second row and third column of 'arr'.

### Ques 7. How to find the shape of a NumPy array?

You can use the attribute 'shape'. For example, 'arr.shape' returns the shape of 'arr'.

### Ques 8. What is the purpose of 'np.eye()' in NumPy?

'np.eye()' creates an identity matrix with ones on the main diagonal and zeros elsewhere.

### Ques 9. How to perform element-wise addition of two NumPy arrays?

import numpy as npnarr1 = np.array([1, 2, 3])narr2 = np.array([4, 5, 6])nresult = arr1 + arr2

### Ques 10. What is the purpose of 'np.arange()' in NumPy?

'np.arange()' creates an array with regularly spaced values within a specified range.

### Ques 11. How to find the mean of a NumPy array?

You can use 'np.mean()'. For example, 'mean_value = np.mean(arr)'.

## Intermediate / 1 to 5 years experienced level questions & answers

### Ques 12. Explain broadcasting in NumPy.

Broadcasting is a powerful mechanism that allows NumPy to work with arrays of different shapes when performing arithmetic operations.

### Ques 13. How to perform element-wise multiplication of two NumPy arrays?

import numpy as npnarr1 = np.array([1, 2, 3])narr2 = np.array([4, 5, 6])nresult = arr1 * arr2

### Ques 14. Explain the purpose of np.random.seed() in NumPy.

np.random.seed() is used to initialize the random number generator in NumPy, ensuring reproducibility of random results.

### Ques 15. Explain the concept of a NumPy universal function (ufunc).

A ufunc in NumPy is a flexible function that operates element-wise on NumPy arrays, supporting broadcasting.

### Ques 16. How to concatenate two NumPy arrays vertically?

You can use 'np.vstack()' or 'np.concatenate()' with 'axis=0'.

### Ques 17. What is the purpose of 'np.ravel()' in NumPy?

'np.ravel()' returns a flattened 1D array from a multi-dimensional array.

### Ques 18. Explain the purpose of 'np.concatenate()' in NumPy.

'np.concatenate()' joins a sequence of arrays along an existing axis.

### Ques 19. How to perform matrix multiplication in NumPy?

You can use 'np.matmul()' or the '@' operator. For example, 'result = np.matmul(arr1, arr2)' or 'result = arr1 @ arr2'.

## Experienced / Expert level questions & answers

### Ques 20. What is the purpose of np.newaxis in NumPy?

np.newaxis is used to increase the dimension of the existing array by one more dimension when used once.

### Ques 21. Explain the differences between np.dot() and np.matmul() in NumPy.

np.dot() performs matrix multiplication for 2-D arrays, while np.matmul() is equivalent to the '@' operator and is more general.

### Ques 22. Create a diagonal matrix using NumPy.

import numpy as npnarr = np.diag([1, 2, 3])

### Ques 23. Explain the purpose of np.meshgrid() in NumPy.

np.meshgrid() is used to create coordinate matrices from coordinate vectors, commonly used for 3D plotting.

### Ques 24. Explain the use of 'np.histogram()' in NumPy.

'np.histogram()' computes the histogram of a set of data, returning the bin counts and bin edges.

### Ques 25. How to find the index of the maximum value in a NumPy array?

You can use 'np.argmax()'. For example, 'np.argmax(arr)' returns the index of the maximum value in 'arr'.

### Ques 26. What is the purpose of 'np.where()' in NumPy?

'np.where()' returns the indices of elements that satisfy a given condition.

### Ques 27. Explain the use of 'np.linalg.inv()' in NumPy.

'np.linalg.inv()' computes the (multiplicative) inverse of a matrix.

### Ques 28. What is the purpose of 'np.percentile()' in NumPy?

'np.percentile()' calculates the nth percentile of a dataset.

### Ques 29. Explain the use of 'np.unique()' in NumPy.

'np.unique()' returns the unique elements of an array.

### Ques 30. How to transpose a NumPy array?

You can use 'arr.T'. For example, 'transposed_arr = arr.T'.