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add exercise with hint

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matianjun1
2017-06-18 22:46:28 +08:00
parent a0e4013bec
commit 453fa9fa14
2 changed files with 472 additions and 190 deletions
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100 Numpy exercises with suggestion.ipynb → 100 Numpy exercises with hint.ipynb
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@@ -4,7 +4,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"# 100 numpy exercises with suggestion\n", "# 100 numpy exercises with hint\n",
"\n", "\n",
"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 exercices for those who teach.\n", "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 exercices for those who teach.\n",
"\n", "\n",
@@ -16,7 +16,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 1. Import the numpy package under the name `np` (★☆☆) (suggestion: import … as ..)" "#### 1. Import the numpy package under the name `np` (★☆☆) \n",
"##### (hint: import … as ..)"
] ]
}, },
{ {
@@ -32,7 +33,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 2. Print the numpy version and the configuration (★☆☆) (suggestion: np.\\_\\_verison\\_\\_, np.show\\_config)" "#### 2. Print the numpy version and the configuration (★☆☆) \n",
"##### (hint: np.\\_\\_verison\\_\\_, np.show\\_config)"
] ]
}, },
{ {
@@ -48,7 +50,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 3. Create a null vector of size 10 (★☆☆) (suggestion: np.zeros)" "#### 3. Create a null vector of size 10 (★☆☆) \n",
"##### (hint: np.zeros)"
] ]
}, },
{ {
@@ -64,7 +67,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 4. How to find the memory size of any array (★☆☆) (suggestion: size, itemsize)" "#### 4. How to find the memory size of any array (★☆☆) \n",
"##### (hint: size, itemsize)"
] ]
}, },
{ {
@@ -80,7 +84,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) (suggestion: np.info)" "#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) \n",
"##### (hint: np.info)"
] ]
}, },
{ {
@@ -96,7 +101,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) (suggestion: array\\[4\\])" "#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) \n",
"##### (hint: array\\[4\\])"
] ]
}, },
{ {
@@ -112,7 +118,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) (suggestion: np.arange)" "#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) \n",
"##### (hint: np.arange)"
] ]
}, },
{ {
@@ -128,7 +135,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 8. Reverse a vector (first element becomes last) (★☆☆) (suggestion: array\\[::-1\\])" "#### 8. Reverse a vector (first element becomes last) (★☆☆) \n",
"##### (hint: array\\[::-1\\])"
] ]
}, },
{ {
@@ -144,7 +152,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) (suggestion: reshape)" "#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) \n",
"##### (hint: reshape)"
] ]
}, },
{ {
@@ -160,7 +169,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 10. Find indices of non-zero elements from \\[1,2,0,0,4,0\\] (★☆☆) (suggestion: np.nonzero)" "#### 10. Find indices of non-zero elements from \\[1,2,0,0,4,0\\] (★☆☆) \n",
"##### (hint: np.nonzero)"
] ]
}, },
{ {
@@ -176,7 +186,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 11. Create a 3x3 identity matrix (★☆☆) (suggestion: np.eye)" "#### 11. Create a 3x3 identity matrix (★☆☆) \n",
"##### (hint: np.eye)"
] ]
}, },
{ {
@@ -192,7 +203,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 12. Create a 3x3x3 array with random values (★☆☆) (suggestion: np.random.random)" "#### 12. Create a 3x3x3 array with random values (★☆☆) \n",
"##### (hint: np.random.random)"
] ]
}, },
{ {
@@ -208,7 +220,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) (suggestion: min, max)" "#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) \n",
"##### (hint: min, max)"
] ]
}, },
{ {
@@ -224,7 +237,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 14. Create a random vector of size 30 and find the mean value (★☆☆) (suggestion: mean)" "#### 14. Create a random vector of size 30 and find the mean value (★☆☆) \n",
"##### (hint: mean)"
] ]
}, },
{ {
@@ -240,7 +254,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) (suggestion: array\\[1:-1, 1:-1\\])" "#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) \n",
"##### (hint: array\\[1:-1, 1:-1\\])"
] ]
}, },
{ {
@@ -256,7 +271,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) (suggestion: np.pad)" "#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) \n",
"##### (hint: np.pad)"
] ]
}, },
{ {
@@ -272,7 +288,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 17. What is the result of the following expression? (★☆☆) (suggestion: NaN = not a number, inf = infinity)" "#### 17. What is the result of the following expression? (★☆☆) \n",
"##### (hint: NaN = not a number, inf = infinity)"
] ]
}, },
{ {
@@ -301,7 +318,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) (suggestion: np.diag)" "#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) \n",
"##### (hint: np.diag)"
] ]
}, },
{ {
@@ -317,7 +335,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) (suggestion: array\\[::2\\])" "#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) \n",
"##### (hint: array\\[::2\\])"
] ]
}, },
{ {
@@ -333,7 +352,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? (suggestion: np.unravel_index)" "#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? \n",
"##### (hint: np.unravel_index)"
] ]
}, },
{ {
@@ -349,7 +369,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) (suggestion: np.tile)" "#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) \n",
"##### (hint: np.tile)"
] ]
}, },
{ {
@@ -365,7 +386,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 22. Normalize a 5x5 random matrix (★☆☆) (suggestion: (x - min) / (max - min))" "#### 22. Normalize a 5x5 random matrix (★☆☆) \n",
"##### (hint: (x - min) / (max - min))"
] ]
}, },
{ {
@@ -381,7 +403,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) (suggestion: np.dtype)" "#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) \n",
"##### (hint: np.dtype)"
] ]
}, },
{ {
@@ -397,7 +420,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) (suggestion: np.dot | @)" "#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) \n",
"##### (hint: np.dot | @)"
] ]
}, },
{ {
@@ -413,7 +437,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) (suggestion: >, <=)" "#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) \n",
"##### (hint: >, <=)"
] ]
}, },
{ {
@@ -429,7 +454,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 26. What is the output of the following script? (★☆☆) (suggestion: np.sum)" "#### 26. What is the output of the following script? (★☆☆) \n",
"##### (hint: np.sum)"
] ]
}, },
{ {
@@ -515,7 +541,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 29. How to round away from zero a float array ? (★☆☆) (suggestion: np.uniform, np.copysign, np.ceil, np.abs)" "#### 29. How to round away from zero a float array ? (★☆☆) \n",
"##### (hint: np.uniform, np.copysign, np.ceil, np.abs)"
] ]
}, },
{ {
@@ -531,7 +558,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 30. How to find common values between two arrays? (★☆☆) (suggestion: np.intersect1d)" "#### 30. How to find common values between two arrays? (★☆☆) \n",
"##### (hint: np.intersect1d)"
] ]
}, },
{ {
@@ -547,7 +575,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) (suggestion: np.seterr, np.errstate)" "#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) \n",
"##### (hint: np.seterr, np.errstate)"
] ]
}, },
{ {
@@ -563,7 +592,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 32. Is the following expressions true? (★☆☆) (suggestion: imaginary number)" "#### 32. Is the following expressions true? (★☆☆) \n",
"##### (hint: imaginary number)"
] ]
}, },
{ {
@@ -588,7 +618,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) (suggestion: np.datetime64, np.timedelta64)" "#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) \n",
"##### (hint: np.datetime64, np.timedelta64)"
] ]
}, },
{ {
@@ -604,7 +635,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) (suggestion: np.arange(dtype=datetime64\\['D'\\]))" "#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) \n",
"##### (hint: np.arange(dtype=datetime64\\['D'\\]))"
] ]
}, },
{ {
@@ -620,7 +652,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 35. How to compute ((A+B)\\*(-A/2)) in place (without copy)? (★★☆) (suggestion: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=))" "#### 35. How to compute ((A+B)\\*(-A/2)) in place (without copy)? (★★☆) \n",
"##### (hint: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=))"
] ]
}, },
{ {
@@ -636,7 +669,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 36. Extract the integer part of a random array using 5 different methods (★★☆) (suggestion: %, np.floor, np.ceil, astype, np.trunc)" "#### 36. Extract the integer part of a random array using 5 different methods (★★☆) \n",
"##### (hint: %, np.floor, np.ceil, astype, np.trunc)"
] ]
}, },
{ {
@@ -652,7 +686,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) (suggestion: np.arange)" "#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) \n",
"##### (hint: np.arange)"
] ]
}, },
{ {
@@ -668,7 +703,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) (suggestion: np.fromiter)" "#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) \n",
"##### (hint: np.fromiter)"
] ]
}, },
{ {
@@ -684,7 +720,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) (suggestion: np.linespace)" "#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) \n",
"##### (hint: np.linespace)"
] ]
}, },
{ {
@@ -700,7 +737,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 40. Create a random vector of size 10 and sort it (★★☆) (suggestion: sort)" "#### 40. Create a random vector of size 10 and sort it (★★☆) \n",
"##### (hint: sort)"
] ]
}, },
{ {
@@ -716,7 +754,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 41. How to sum a small array faster than np.sum? (★★☆) (suggestion: np.add.reduce)" "#### 41. How to sum a small array faster than np.sum? (★★☆) \n",
"##### (hint: np.add.reduce)"
] ]
}, },
{ {
@@ -732,7 +771,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 42. Consider two random array A and B, check if they are equal (★★☆) (suggestion: np.allclose, np.array\\_equal)" "#### 42. Consider two random array A and B, check if they are equal (★★☆) \n",
"##### (hint: np.allclose, np.array\\_equal)"
] ]
}, },
{ {
@@ -748,7 +788,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 43. Make an array immutable (read-only) (★★☆) (suggestion: flags.writeable)" "#### 43. Make an array immutable (read-only) (★★☆) \n",
"##### (hint: flags.writeable)"
] ]
}, },
{ {
@@ -764,7 +805,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) (suggestion: np.sqrt, np.arctan2)" "#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) \n",
"##### (hint: np.sqrt, np.arctan2)"
] ]
}, },
{ {
@@ -780,7 +822,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) (suggestion: argmax)" "#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) \n",
"##### (hint: argmax)"
] ]
}, },
{ {
@@ -796,7 +839,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 46. Create a structured array with `x` and `y` coordinates covering the \\[0,1\\]x\\[0,1\\] area (★★☆) (suggestion: np.meshgrid)" "#### 46. Create a structured array with `x` and `y` coordinates covering the \\[0,1\\]x\\[0,1\\] area (★★☆) \n",
"##### (hint: np.meshgrid)"
] ]
}, },
{ {
@@ -812,7 +856,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) (suggestion: np.subtract.outer)" "#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) \n",
"##### (hint: np.subtract.outer)"
] ]
}, },
{ {
@@ -828,7 +873,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) (suggestion: np.iinfo, np.finfo, eps)" "#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) \n",
"##### (hint: np.iinfo, np.finfo, eps)"
] ]
}, },
{ {
@@ -844,7 +890,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 49. How to print all the values of an array? (★★☆) (suggestion: np.set\\_printoptions)" "#### 49. How to print all the values of an array? (★★☆) \n",
"##### (hint: np.set\\_printoptions)"
] ]
}, },
{ {
@@ -860,7 +907,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) (suggestion: argmin)" "#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) \n",
"##### (hint: argmin)"
] ]
}, },
{ {
@@ -876,7 +924,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) (suggestion: dtype)" "#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) \n",
"##### (hint: dtype)"
] ]
}, },
{ {
@@ -892,7 +941,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) (suggestion: np.atleast\\_2d, T, np.sqrt)" "#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) \n",
"##### (hint: np.atleast\\_2d, T, np.sqrt)"
] ]
}, },
{ {
@@ -908,7 +958,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? (suggestion: astype(copy=False))" "#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? \n",
"##### (hint: astype(copy=False))"
] ]
}, },
{ {
@@ -924,7 +975,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 54. How to read the following file? (★★☆) (suggestion: np.genfromtxt)" "#### 54. How to read the following file? (★★☆) \n",
"##### (hint: np.genfromtxt)"
] ]
}, },
{ {
@@ -951,7 +1003,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) (suggestion: np.ndenumerate, np.ndindex)" "#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) \n",
"##### (hint: np.ndenumerate, np.ndindex)"
] ]
}, },
{ {
@@ -967,7 +1020,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 56. Generate a generic 2D Gaussian-like array (★★☆) (suggestion: np.meshgrid, np.exp)" "#### 56. Generate a generic 2D Gaussian-like array (★★☆) \n",
"##### (hint: np.meshgrid, np.exp)"
] ]
}, },
{ {
@@ -983,7 +1037,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 57. How to randomly place p elements in a 2D array? (★★☆) (suggestion: np.put, np.random.choice)" "#### 57. How to randomly place p elements in a 2D array? (★★☆) \n",
"##### (hint: np.put, np.random.choice)"
] ]
}, },
{ {
@@ -999,7 +1054,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 58. Subtract the mean of each row of a matrix (★★☆) (suggestion: mean(axis=,keepdims=))" "#### 58. Subtract the mean of each row of a matrix (★★☆) \n",
"##### (hint: mean(axis=,keepdims=))"
] ]
}, },
{ {
@@ -1015,7 +1071,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 59. How to sort an array by the nth column? (★★☆) (suggestion: argsort)" "#### 59. How to sort an array by the nth column? (★★☆) \n",
"##### (hint: argsort)"
] ]
}, },
{ {
@@ -1031,7 +1088,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 60. How to tell if a given 2D array has null columns? (★★☆) (suggestion: any, ~)" "#### 60. How to tell if a given 2D array has null columns? (★★☆) \n",
"##### (hint: any, ~)"
] ]
}, },
{ {
@@ -1047,7 +1105,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 61. Find the nearest value from a given value in an array (★★☆) (suggestion: np.abs, argmin, flat)" "#### 61. Find the nearest value from a given value in an array (★★☆) \n",
"##### (hint: np.abs, argmin, flat)"
] ]
}, },
{ {
@@ -1063,7 +1122,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) (suggestion: np.nditer)" "#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) \n",
"##### (hint: np.nditer)"
] ]
}, },
{ {
@@ -1079,7 +1139,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 63. Create an array class that has a name attribute (★★☆) (suggestion: class method)" "#### 63. Create an array class that has a name attribute (★★☆) \n",
"##### (hint: class method)"
] ]
}, },
{ {
@@ -1095,7 +1156,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) (suggestion: np.bincount | np.add.at)" "#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) \n",
"##### (hint: np.bincount | np.add.at)"
] ]
}, },
{ {
@@ -1111,7 +1173,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) (suggestion: np.bincount)" "#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) \n",
"##### (hint: np.bincount)"
] ]
}, },
{ {
@@ -1127,7 +1190,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) (suggestion: np.unique)" "#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) \n",
"##### (hint: np.unique)"
] ]
}, },
{ {
@@ -1143,7 +1207,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) (suggestion: sum(axis=(-2,-1)))" "#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) \n",
"##### (hint: sum(axis=(-2,-1)))"
] ]
}, },
{ {
@@ -1159,7 +1224,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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? (★★★) (suggestion: np.bincount)" "#### 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? (★★★) \n",
"##### (hint: np.bincount)"
] ]
}, },
{ {
@@ -1175,7 +1241,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 69. How to get the diagonal of a dot product? (★★★) (suggestion: np.diag)" "#### 69. How to get the diagonal of a dot product? (★★★) \n",
"##### (hint: np.diag)"
] ]
}, },
{ {
@@ -1191,7 +1258,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 70. Consider the vector \\[1, 2, 3, 4, 5\\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) (suggestion: array\\[::4\\])" "#### 70. Consider the vector \\[1, 2, 3, 4, 5\\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) \n",
"##### (hint: array\\[::4\\])"
] ]
}, },
{ {
@@ -1207,7 +1275,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) (suggestion: array\\[:, :, None\\])" "#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) \n",
"##### (hint: array\\[:, :, None\\])"
] ]
}, },
{ {
@@ -1223,7 +1292,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 72. How to swap two rows of an array? (★★★) (suggestion: array\\[\\[\\]\\] = array\\[\\[\\]\\])" "#### 72. How to swap two rows of an array? (★★★) \n",
"##### (hint: array\\[\\[\\]\\] = array\\[\\[\\]\\])"
] ]
}, },
{ {
@@ -1239,7 +1309,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) (suggestion: repeat, np.roll, np.sort, view, np.unique)" "#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) \n",
"##### (hint: repeat, np.roll, np.sort, view, np.unique)"
] ]
}, },
{ {
@@ -1255,7 +1326,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) (suggestion: np.repeat)" "#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) \n",
"##### (hint: np.repeat)"
] ]
}, },
{ {
@@ -1271,7 +1343,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 75. How to compute averages using a sliding window over an array? (★★★) (suggestion: np.cumsum)" "#### 75. How to compute averages using a sliding window over an array? (★★★) \n",
"##### (hint: np.cumsum)"
] ]
}, },
{ {
@@ -1287,7 +1360,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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\\]) (★★★) (suggestion: from numpy.lib import stride_tricks)" "#### 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\\]) (★★★) \n",
"##### (hint: from numpy.lib import stride_tricks)"
] ]
}, },
{ {
@@ -1303,7 +1377,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) (suggestion: np.logical_not, np.negative)" "#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) \n",
"##### (hint: np.logical_not, np.negative)"
] ]
}, },
{ {
@@ -1351,7 +1426,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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) (★★★) (suggestion: minimum, maximum)" "#### 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) (★★★) \n",
"##### (hint: minimum, maximum)"
] ]
}, },
{ {
@@ -1367,7 +1443,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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\\]\\]? (★★★) (suggestion: stride\\_tricks.as\\_strided)" "#### 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\\]\\]? (★★★) \n",
"##### (hint: stride\\_tricks.as\\_strided)"
] ]
}, },
{ {
@@ -1383,7 +1460,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 82. Compute a matrix rank (★★★) (suggestion: np.linalg.svd) (suggestion: np.linalg.svd)" "#### 82. Compute a matrix rank (★★★) \n",
"##### (hint: np.linalg.svd) (suggestion: np.linalg.svd)"
] ]
}, },
{ {
@@ -1399,7 +1477,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 83. How to find the most frequent value in an array? (suggestion: np.bincount, argmax)" "#### 83. How to find the most frequent value in an array? \n",
"##### (hint: np.bincount, argmax)"
] ]
}, },
{ {
@@ -1415,7 +1494,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) (suggestion: stride\\_tricks.as\\_strided)" "#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) \n",
"##### (hint: stride\\_tricks.as\\_strided)"
] ]
}, },
{ {
@@ -1431,7 +1511,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 85. Create a 2D array subclass such that Z\\[i,j\\] == Z\\[j,i\\] (★★★) (suggestion: class method)" "#### 85. Create a 2D array subclass such that Z\\[i,j\\] == Z\\[j,i\\] (★★★) \n",
"##### (hint: class method)"
] ]
}, },
{ {
@@ -1447,7 +1528,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 86. Consider a set of p matrices wich 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)) (★★★) (suggestion: np.tensordot)" "#### 86. Consider a set of p matrices wich 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)) (★★★) \n",
"##### (hint: np.tensordot)"
] ]
}, },
{ {
@@ -1463,7 +1545,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) (suggestion: np.add.reduceat)" "#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) \n",
"##### (hint: np.add.reduceat)"
] ]
}, },
{ {
@@ -1495,7 +1578,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 89. How to get the n largest values of an array (★★★) (suggestion: np.argsort | np.argpartition)" "#### 89. How to get the n largest values of an array (★★★) \n",
"##### (hint: np.argsort | np.argpartition)"
] ]
}, },
{ {
@@ -1511,7 +1595,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) (suggestion: np.indices)" "#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) \n",
"##### (hint: np.indices)"
] ]
}, },
{ {
@@ -1528,7 +1613,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 91. How to create a record array from a regular array? (★★★) (suggestion: np.core.records.fromarrays)" "#### 91. How to create a record array from a regular array? (★★★) \n",
"##### (hint: np.core.records.fromarrays)"
] ]
}, },
{ {
@@ -1544,7 +1630,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) (suggestion: np.power, \\*, np.einsum)" "#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) \n",
"##### (hint: np.power, \\*, np.einsum)"
] ]
}, },
{ {
@@ -1560,7 +1647,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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? (★★★) (suggestion: np.where)" "#### 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? (★★★) \n",
"##### (hint: np.where)"
] ]
}, },
{ {
@@ -1592,7 +1680,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 95. Convert a vector of ints into a matrix binary representation (★★★) (suggestion: np.unpackbits)" "#### 95. Convert a vector of ints into a matrix binary representation (★★★) \n",
"##### (hint: np.unpackbits)"
] ]
}, },
{ {
@@ -1608,7 +1697,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 96. Given a two dimensional array, how to extract unique rows? (★★★) (suggestion: np.ascontiguousarray)" "#### 96. Given a two dimensional array, how to extract unique rows? (★★★) \n",
"##### (hint: np.ascontiguousarray)"
] ]
}, },
{ {
@@ -1624,7 +1714,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) (suggestion: np.einsum)" "#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) \n",
"##### (hint: np.einsum)"
] ]
}, },
{ {
@@ -1640,7 +1731,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? (suggestion: np.cumsum, np.interp)" "#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? \n",
"##### (hint: np.cumsum, np.interp)"
] ]
}, },
{ {
@@ -1656,7 +1748,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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. (★★★) (suggestion: np.logical\\_and.reduce, np.mod)" "#### 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. (★★★) \n",
"##### (hint: np.logical\\_and.reduce, np.mod)"
] ]
}, },
{ {
@@ -1672,7 +1765,8 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"#### 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). (★★★) (suggestion: np.percentile)" "#### 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). (★★★) \n",
"##### (hint: np.percentile)"
] ]
}, },
{ {

378
100 Numpy exercises with suggestion.md → 100 Numpy exercises with hint.md
View File

@@ -1,5 +1,5 @@
# 100 numpy exercises with suggestion # 100 numpy exercises with hint
This is a collection of exercises that have been collected in the numpy mailing This is a collection of exercises that have been collected in the numpy mailing
list, on stack overflow and in the numpy documentation. I've also created some list, on stack overflow and in the numpy documentation. I've also created some
@@ -10,71 +10,105 @@ those who teach.
If you find an error or think you've a better way to solve some of them, feel If you find an error or think you've a better way to solve some of them, feel
free to open an issue at <https://github.com/rougier/numpy-100> free to open an issue at <https://github.com/rougier/numpy-100>
#### 1. Import the numpy package under the name `np` (★☆☆) (suggestion: import … as ..) #### 1. Import the numpy package under the name `np` (★☆☆)
##### (hint: import … as ..)
#### 2. Print the numpy version and the configuration (★☆☆) (suggestion: np.\_\_verison\_\_, np.show\_config) #### 2. Print the numpy version and the configuration (★☆☆)
##### (hint: np.\_\_verison\_\_, np.show\_config)
#### 3. Create a null vector of size 10 (★☆☆) (suggestion: np.zeros) #### 3. Create a null vector of size 10 (★☆☆)
##### (hint: np.zeros)
#### 4. How to find the memory size of any array (★☆☆) (suggestion: size, itemsize) #### 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? (★☆☆) (suggestion: np.info) #### 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 (★☆☆) (suggestion: array\[4\]) #### 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 (★☆☆) (suggestion: np.arange) #### 7. Create a vector with values ranging from 10 to 49 (★☆☆)
##### (hint: np.arange)
#### 8. Reverse a vector (first element becomes last) (★☆☆) (suggestion: array\[::-1\]) #### 8. Reverse a vector (first element becomes last) (★☆☆)
##### (hint: array\[::-1\])
#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) (suggestion: reshape) #### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆)
##### (hint: reshape)
#### 10. Find indices of non-zero elements from \[1,2,0,0,4,0\] (★☆☆) (suggestion: np.nonzero) #### 10. Find indices of non-zero elements from \[1,2,0,0,4,0\] (★☆☆)
##### (hint: np.nonzero)
#### 11. Create a 3x3 identity matrix (★☆☆) (suggestion: np.eye) #### 11. Create a 3x3 identity matrix (★☆☆)
##### (hint: np.eye)
#### 12. Create a 3x3x3 array with random values (★☆☆) (suggestion: np.random.random) #### 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 (★☆☆) (suggestion: min, max) #### 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 (★☆☆) (suggestion: mean) #### 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 (★☆☆) (suggestion: array\[1:-1, 1:-1\]) #### 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 0's) around an existing array? (★☆☆) (suggestion: np.pad) #### 16. How to add a border (filled with 0's) around an existing array? (★☆☆)
##### (hint: np.pad)
#### 17. What is the result of the following expression? (★☆☆) (suggestion: NaN = not a number, inf = infinity) #### 17. What is the result of the following expression? (★☆☆)
##### (hint: NaN = not a number, inf = infinity)
```python ```python
@@ -85,39 +119,57 @@ np.nan - np.nan
0.3 == 3 * 0.1 0.3 == 3 * 0.1
``` ```
#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) (suggestion: np.diag) #### 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 (★☆☆) (suggestion: array\[::2\]) #### 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? (suggestion: np.unravel\_index) #### 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 (★☆☆) (suggestion: np.tile) #### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆)
##### (hint: np.tile)
#### 22. Normalize a 5x5 random matrix (★☆☆) (suggestion: (x - min) / (max - min)) #### 22. Normalize a 5x5 random matrix (★☆☆)
##### (hint: (x - min) / (max - min))
#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) (suggestion: np.dtype) #### 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) (★☆☆) (suggestion: np.dot | @) #### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆)
##### (hint: np.dot | @)
#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) (suggestion: >, <=) #### 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? (★☆☆) (suggestion: np.sum) #### 26. What is the output of the following script? (★☆☆)
##### (hint: np.sum)
```python ```python
@@ -149,110 +201,162 @@ np.array(0) // np.array(0)
np.array([np.nan]).astype(int).astype(float) np.array([np.nan]).astype(int).astype(float)
``` ```
#### 29. How to round away from zero a float array ? (★☆☆) (suggestion: np.uniform, np.copysign, np.ceil, np.abs) #### 29. How to round away from zero a float array ? (★☆☆)
##### (hint: np.uniform, np.copysign, np.ceil, np.abs)
#### 30. How to find common values between two arrays? (★☆☆) (suggestion: np.intersect1d) #### 30. How to find common values between two arrays? (★☆☆)
##### (hint: np.intersect1d)
#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) (suggestion: np.seterr, np.errstate) #### 31. How to ignore all numpy warnings (not recommended)? (★☆☆)
##### (hint: np.seterr, np.errstate)
#### 32. Is the following expressions true? (★☆☆) (suggestion: imaginary number) #### 32. Is the following expressions true? (★☆☆)
##### (hint: imaginary number)
```python ```python
np.sqrt(-1) == np.emath.sqrt(-1) np.sqrt(-1) == np.emath.sqrt(-1)
``` ```
#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) (suggestion: np.datetime64, np.timedelta64) #### 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? (★★☆) (suggestion: np.arange(dtype=datetime64\['D'\])) #### 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)? (★★☆) (suggestion: np.add(out=), np.negative(out=), np.multiply(out=), np.divide(out=)) #### 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 using 5 different methods (★★☆) (suggestion: %, np.floor, np.ceil, astype, np.trunc) #### 36. Extract the integer part of a random array using 5 different methods (★★☆)
##### (hint: %, np.floor, np.ceil, astype, np.trunc)
#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) (suggestion: np.arange) #### 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 (★☆☆) (suggestion: np.fromiter) #### 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 (★★☆) (suggestion: np.linespace) #### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆)
##### (hint: np.linespace)
#### 40. Create a random vector of size 10 and sort it (★★☆) (suggestion: sort) #### 40. Create a random vector of size 10 and sort it (★★☆)
##### (hint: sort)
#### 41. How to sum a small array faster than np.sum? (★★☆) (suggestion: np.add.reduce) #### 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 (★★☆) (suggestion: np.allclose, np.array\_equal) #### 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) (★★☆) (suggestion: flags.writeable) #### 43. Make an array immutable (read-only) (★★☆)
##### (hint: flags.writeable)
#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) (suggestion: np.sqrt, np.arctan2) #### 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 (★★☆) (suggestion: argmax) #### 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 (★★☆) (suggestion: np.meshgrid) #### 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)) (suggestion: np.subtract.outer) #### 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 (★★☆) (suggestion: np.iinfo, np.finfo, eps) #### 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? (★★☆) (suggestion: np.set\_printoptions) #### 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? (★★☆) (suggestion: argmin) #### 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) (★★☆) (suggestion: dtype) #### 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 (★★☆) (suggestion: np.atleast\_2d, T, np.sqrt) #### 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? (suggestion: astype(copy=False)) #### 53. How to convert a float (32 bits) array into an integer (32 bits) in place?
##### (hint: astype(copy=False))
#### 54. How to read the following file? (★★☆) (suggestion: np.genfromtxt) #### 54. How to read the following file? (★★☆)
##### (hint: np.genfromtxt)
``` ```
@@ -261,95 +365,141 @@ np.sqrt(-1) == np.emath.sqrt(-1)
, , 9,10,11 , , 9,10,11
``` ```
#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) (suggestion: np.ndenumerate, np.ndindex) #### 55. What is the equivalent of enumerate for numpy arrays? (★★☆)
##### (hint: np.ndenumerate, np.ndindex)
#### 56. Generate a generic 2D Gaussian-like array (★★☆) (suggestion: np.meshgrid, np.exp)
#### 56. Generate a generic 2D Gaussian-like array (★★☆)
##### (hint: np.meshgrid, np.exp)
#### 57. How to randomly place p elements in a 2D array? (★★☆) (suggestion: np.put, np.random.choice)
#### 57. How to randomly place p elements in a 2D array? (★★☆)
#### 58. Subtract the mean of each row of a matrix (★★☆) (suggestion: mean(axis=,keepdims=)) ##### (hint: np.put, np.random.choice)
#### 59. How to sort an array by the nth column? (★★☆) (suggestion: argsort) #### 58. Subtract the mean of each row of a matrix (★★☆)
##### (hint: mean(axis=,keepdims=))
#### 60. How to tell if a given 2D array has null columns? (★★☆) (suggestion: any, ~)
#### 59. How to sort an array by the nth column? (★★☆)
##### (hint: argsort)
#### 61. Find the nearest value from a given value in an array (★★☆) (suggestion: np.abs, argmin, flat)
#### 60. How to tell if a given 2D array has null columns? (★★☆)
#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) (suggestion: np.nditer) ##### (hint: any, ~)
#### 63. Create an array class that has a name attribute (★★☆) (suggestion: class method) #### 61. Find the nearest value from a given value in an array (★★☆)
##### (hint: np.abs, argmin, flat)
#### 64. Consider a given vector, how to add 1 to each element indexed by a second vector (be careful with repeated indices)? (★★★) (suggestion: np.bincount | np.add.at)
#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆)
##### (hint: np.nditer)
#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) (suggestion: np.bincount)
#### 63. Create an array class that has a name attribute (★★☆)
#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) (suggestion: np.unique) ##### (hint: class method)
#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) (suggestion: sum(axis=(-2,-1))) #### 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)
#### 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? (★★★) (suggestion: np.bincount)
#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★)
##### (hint: np.bincount)
#### 69. How to get the diagonal of a dot product? (★★★) (suggestion: np.diag)
#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★)
#### 70. Consider the vector \[1, 2, 3, 4, 5\], how to build a new vector with 3 consecutive zeros interleaved between each value? (★★★) (suggestion: array\[::4\]) ##### (hint: np.unique)
#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) (suggestion: array\[:, :, None\]) #### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★)
##### (hint: sum(axis=(-2,-1)))
#### 72. How to swap two rows of an array? (★★★) (suggestion: array\[\[\]\] = array\[\[\]\])
#### 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)
#### 73. Consider a set of 10 triplets describing 10 triangles (with shared vertices), find the set of unique line segments composing all the triangles (★★★) (suggestion: repeat, np.roll, np.sort, view, np.unique)
#### 69. How to get the diagonal of a dot product? (★★★)
#### 74. Given an array C that is a bincount, how to produce an array A such that np.bincount(A) == C? (★★★) (suggestion: np.repeat) ##### (hint: np.diag)
#### 75. How to compute averages using a sliding window over an array? (★★★) (suggestion: np.cumsum) #### 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\[::4\])
#### 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\[-1\]) (★★★) (suggestion: from numpy.lib import stride\_tricks)
#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★)
##### (hint: array\[:, :, None\])
#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) (suggestion: np.logical_not, np.negative)
#### 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 an array C that is 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)
#### 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)
#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★)
##### (hint: np.logical_not, np.negative)
@@ -361,35 +511,51 @@ np.sqrt(-1) == np.emath.sqrt(-1)
#### 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) (★★★) (suggestion: minimum, maximum) #### 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 = \[\[1,2,3,4\], \[2,3,4,5\], \[3,4,5,6\], ..., \[11,12,13,14\]\]? (★★★) (suggestion: stride\_tricks.as\_strided) #### 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)
#### 82. Compute a matrix rank (★★★) (suggestion: np.linalg.svd) #### 82. Compute a matrix rank (★★★)
##### (hint: np.linalg.svd)
#### 83. How to find the most frequent value in an array? (suggestion: np.bincount, argmax) #### 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 (★★★) (suggestion: stride\_tricks.as\_strided) #### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★)
##### (hint: stride\_tricks.as\_strided)
#### 85. Create a 2D array subclass such that Z\[i,j\] == Z\[j,i\] (★★★) (suggestion: class method) #### 85. Create a 2D array subclass such that Z\[i,j\] == Z\[j,i\] (★★★)
##### (hint: class method)
#### 86. Consider a set of p matrices wich 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)) (★★★) (suggestion: np.tensordot) #### 86. Consider a set of p matrices wich 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)? (★★★) (suggestion: np.add.reduceat) #### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★)
##### (hint: np.add.reduceat)
@@ -397,23 +563,33 @@ np.sqrt(-1) == np.emath.sqrt(-1)
#### 89. How to get the n largest values of an array (★★★) (suggestion: np.argsort | np.argpartition) #### 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) (★★★) (suggestion: np.indices) #### 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? (★★★) (suggestion: np.core.records.fromarrays) #### 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 (★★★) (suggestion: np.power, \*, np.einsum) #### 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? (★★★) (suggestion: np.where) #### 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)
@@ -421,25 +597,37 @@ np.sqrt(-1) == np.emath.sqrt(-1)
#### 95. Convert a vector of ints into a matrix binary representation (★★★) (suggestion: np.unpackbits) #### 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? (★★★) (suggestion: np.ascontiguousarray) #### 96. Given a two dimensional array, how to extract unique rows? (★★★)
##### (hint: np.ascontiguousarray)
#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) (suggestion: np.einsum) #### 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 (★★★)? (suggestion: np.cumsum, np.interp) #### 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. (★★★) (suggestion: np.logical\_and.reduce, np.mod) #### 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). (★★★) (suggestion: np.percentile) #### 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)