numpy-100/100_Numpy_exercises_with_hints.md
2023-04-03 09:26:02 +02:00

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100 numpy exercises

This is a collection of exercises that have been collected in the numpy mailing list, on stack overflow and in the numpy documentation. The goal of this collection is to offer a quick reference for both old and new users but also to provide a set of exercises for those who teach.

If you find an error or think youve a better way to solve some of them, feel free to open an issue at https://github.com/rougier/numpy-100. File automatically generated. See the documentation to update questions/answers/hints programmatically.

1. Import the numpy package under the name np (★☆☆)

hint: import … as #### 2. Print the numpy version and the configuration (★☆☆) hint: np.__version__, np.show_config) #### 3. Create a null vector of size 10 (★☆☆) hint: np.zeros #### 4. How to find the memory size of any array (★☆☆) hint: size, itemsize #### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) hint: np.info #### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) hint: array[4] #### 7. Create a vector with values ranging from 10 to 49 (★☆☆) hint: arange #### 8. Reverse a vector (first element becomes last) (★☆☆) hint: array[::-1] #### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) hint: reshape #### 10. Find indices of non-zero elements from [1,2,0,0,4,0] (★☆☆) hint: np.nonzero #### 11. Create a 3x3 identity matrix (★☆☆) hint: np.eye #### 12. Create a 3x3x3 array with random values (★☆☆) hint: np.random.random #### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) hint: min, max #### 14. Create a random vector of size 30 and find the mean value (★☆☆) hint: mean #### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) hint: array[1:-1, 1:-1] #### 16. How to add a border (filled with 0s) around an existing array? (★☆☆) hint: np.pad #### 17. What is the result of the following expression? (★☆☆)

0 * np.nan
np.nan == np.nan
np.inf > np.nan
np.nan - np.nan
np.nan in set([np.nan])
0.3 == 3 * 0.1

hint: NaN = not a number, inf = infinity #### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) hint: np.diag #### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) hint: array[::2] #### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (★☆☆) hint: np.unravel_index #### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) hint: np.tile #### 22. Normalize a 5x5 random matrix (★☆☆) hint: (x -mean)/std #### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) hint: np.dtype #### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) hint: #### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) hint: >, < #### 26. What is the output of the following script? (★☆☆)

# Author: Jake VanderPlas

print(sum(range(5),-1))
from numpy import *
print(sum(range(5),-1))

hint: np.sum #### 27. Consider an integer vector Z, which of these expressions are legal? (★☆☆)

Z**Z
2 << Z >> 2
Z <- Z
1j*Z
Z/1/1
Z<Z>Z

No hints provided... #### 28. What are the result of the following expressions? (★☆☆)

np.array(0) / np.array(0)
np.array(0) // np.array(0)
np.array([np.nan]).astype(int).astype(float)

No hints provided... #### 29. How to round away from zero a float array ? (★☆☆) hint: np.uniform, np.copysign, np.ceil, np.abs, np.where #### 30. How to find common values between two arrays? (★☆☆) hint: np.intersect1d #### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) hint: np.seterr, np.errstate #### 32. Is the following expressions true? (★☆☆)

np.sqrt(-1) == np.emath.sqrt(-1)

hint: imaginary number #### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) hint: np.datetime64, np.timedelta64 #### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) hint: np.arange(dtype=datetime64['D']) #### 35. How to compute ((A+B)*(-A/2)) in place (without copy)? (★★☆) hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=) #### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆) hint: %, np.floor, astype, np.trunc #### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) hint: np.arange #### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) hint: np.fromiter #### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) hint: np.linspace #### 40. Create a random vector of size 10 and sort it (★★☆) hint: sort #### 41. How to sum a small array faster than np.sum? (★★☆) hint: np.add.reduce #### 42. Consider two random array A and B, check if they are equal (★★☆) hint: np.allclose, np.array_equal #### 43. Make an array immutable (read-only) (★★☆) hint: flags.writeable #### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) hint: np.sqrt, np.arctan2 #### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) hint: argmax #### 46. Create a structured array with x and y coordinates covering the [0,1]x[0,1] area (★★☆) hint: np.meshgrid #### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) (★★☆) hint: np.subtract.outer #### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) hint: np.iinfo, np.finfo, eps #### 49. How to print all the values of an array? (★★☆) hint: np.set_printoptions #### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) hint: argmin #### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) hint: dtype #### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) hint: np.atleast_2d, T, np.sqrt #### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? hint: view and [:] = #### 54. How to read the following file? (★★☆)

1, 2, 3, 4, 5
6,  ,  , 7, 8
 ,  , 9,10,11

hint: np.genfromtxt #### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) hint: np.ndenumerate, np.ndindex #### 56. Generate a generic 2D Gaussian-like array (★★☆) hint: np.meshgrid, np.exp #### 57. How to randomly place p elements in a 2D array? (★★☆) hint: np.put, np.random.choice #### 58. Subtract the mean of each row of a matrix (★★☆) hint: mean(axis=,keepdims=) #### 59. How to sort an array by the nth column? (★★☆) hint: argsort #### 60. How to tell if a given 2D array has null columns? (★★☆) hint: any, ~ #### 61. Find the nearest value from a given value in an array (★★☆) hint: np.abs, argmin, flat #### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) hint: np.nditer #### 63. Create an array class that has a name attribute (★★☆) hint: class method #### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) hint: np.bincount | np.add.at #### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) hint: np.bincount #### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★☆) hint: np.unique #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) hint: sum(axis=(-2,-1)) #### 68. Considering a one-dimensional vector D, how to compute means of subsets of D using a vector S of same size describing subset indices? (★★★) hint: np.bincount #### 69. How to get the diagonal of a dot product? (★★★) hint: np.diag #### 70. Consider the vector [1, 2, 3, 4, 5], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) hint: array[::4] #### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) hint: array[:, :, None] #### 72. How to swap two rows of an array? (★★★) hint: array[[]] = array[[]] #### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) hint: repeat, np.roll, np.sort, view, np.unique #### 74. Given a sorted array C that corresponds to a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) hint: np.repeat #### 75. How to compute averages using a sliding window over an array? (★★★) hint: np.cumsum, from numpy.lib.stride_tricks import sliding_window_view (np>=1.20.0) #### 76. Consider a one-dimensional array Z, build a two-dimensional array whose first row is (Z[0],Z[1],Z[2]) and each subsequent row is shifted by 1 (last row should be (Z[-3],Z[-2],Z[-1]) (★★★) hint: from numpy.lib import stride_tricks, from numpy.lib.stride_tricks import sliding_window_view (np>=1.20.0) #### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) hint: np.logical_not, np.negative #### 78. Consider 2 sets of points P0,P1 describing lines (2d) and a point p, how to compute distance from p to each line i (P0[i],P1[i])? (★★★) No hints provided... #### 79. Consider 2 sets of points P0,P1 describing lines (2d) and a set of points P, how to compute distance from each point j (P[j]) to each line i (P0[i],P1[i])? (★★★) No hints provided... #### 80. Consider an arbitrary array, write a function that extract a subpart with a fixed shape and centered on a given element (pad with a fill value when necessary) (★★★) hint: minimum maximum #### 81. Consider an array Z = [1,2,3,4,5,6,7,8,9,10,11,12,13,14], how to generate an array R = 1,2,3,4], [2,3,4,5], [3,4,5,6], …, [11,12,13,14? (★★★) hint: stride_tricks.as_strided, from numpy.lib.stride_tricks import sliding_window_view (np>=1.20.0) #### 82. Compute a matrix rank (★★★) hint: np.linalg.svd, np.linalg.matrix_rank #### 83. How to find the most frequent value in an array? hint: np.bincount, argmax #### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) hint: stride_tricks.as_strided, from numpy.lib.stride_tricks import sliding_window_view (np>=1.20.0) #### 85. Create a 2D array subclass such that Z[i,j] == Z[j,i] (★★★) hint: class method #### 86. Consider a set of p matrices with shape (n,n) and a set of p vectors with shape (n,1). How to compute the sum of of the p matrix products at once? (result has shape (n,1)) (★★★) hint: np.tensordot #### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) hint: np.add.reduceat, from numpy.lib.stride_tricks import sliding_window_view (np>=1.20.0) #### 88. How to implement the Game of Life using numpy arrays? (★★★) No hints provided... #### 89. How to get the n largest values of an array (★★★) hint: np.argsort | np.argpartition #### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) hint: np.indices #### 91. How to create a record array from a regular array? (★★★) hint: np.core.records.fromarrays #### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) hint: np.power, *, np.einsum #### 93. Consider two arrays A and B of shape (8,3) and (2,2). How to find rows of A that contain elements of each row of B regardless of the order of the elements in B? (★★★) hint: np.where #### 94. Considering a 10x3 matrix, extract rows with unequal values (e.g. [2,2,3]) (★★★) No hints provided... #### 95. Convert a vector of ints into a matrix binary representation (★★★) hint: np.unpackbits #### 96. Given a two dimensional array, how to extract unique rows? (★★★) hint: np.ascontiguousarray | np.unique #### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) hint: np.einsum #### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? hint: np.cumsum, np.interp #### 99. Given an integer n and a 2D array X, select from X the rows which can be interpreted as draws from a multinomial distribution with n degrees, i.e., the rows which only contain integers and which sum to n. (★★★) hint: np.logical_and.reduce, np.mod #### 100. Compute bootstrapped 95% confidence intervals for the mean of a 1D array X (i.e., resample the elements of an array with replacement N times, compute the mean of each sample, and then compute percentiles over the means). (★★★) hint: np.percentile