diff --git a/100 Numpy exercises with hint.ipynb b/100 Numpy exercises with hint.ipynb new file mode 100644 index 0000000..cc629f2 --- /dev/null +++ b/100 Numpy exercises with hint.ipynb @@ -0,0 +1,1803 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 100 numpy exercises with hint\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", + "\n", + "\n", + "If you find an error or think you've a better way to solve some of them, feel free to open an issue at " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 1. Import the numpy package under the name `np` (★☆☆) \n", + "(**hint**: import … as …)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 2. Print the numpy version and the configuration (★☆☆) \n", + "(**hint**: np.\\_\\_verison\\_\\_, np.show\\_config)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 3. Create a null vector of size 10 (★☆☆) \n", + "(**hint**: np.zeros)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 4. How to find the memory size of any array (★☆☆) \n", + "(**hint**: size, itemsize)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 5. How to get the documentation of the numpy add function from the command line? (★☆☆) \n", + "(**hint**: np.info)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 6. Create a null vector of size 10 but the fifth value which is 1 (★☆☆) \n", + "(**hint**: array\\[4\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 7. Create a vector with values ranging from 10 to 49 (★☆☆) \n", + "(**hint**: np.arange)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 8. Reverse a vector (first element becomes last) (★☆☆) \n", + "(**hint**: array\\[::-1\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 9. Create a 3x3 matrix with values ranging from 0 to 8 (★☆☆) \n", + "(**hint**: reshape)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 10. Find indices of non-zero elements from \\[1,2,0,0,4,0\\] (★☆☆) \n", + "(**hint**: np.nonzero)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 11. Create a 3x3 identity matrix (★☆☆) \n", + "(**hint**: np.eye)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 12. Create a 3x3x3 array with random values (★☆☆) \n", + "(**hint**: np.random.random)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 13. Create a 10x10 array with random values and find the minimum and maximum values (★☆☆) \n", + "(**hint**: min, max)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 14. Create a random vector of size 30 and find the mean value (★☆☆) \n", + "(**hint**: mean)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 15. Create a 2d array with 1 on the border and 0 inside (★☆☆) \n", + "(**hint**: array\\[1:-1, 1:-1\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 16. How to add a border (filled with 0's) around an existing array? (★☆☆) \n", + "(**hint**: np.pad)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 17. What is the result of the following expression? (★☆☆) \n", + "(**hint**: NaN = not a number, inf = infinity)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```python\n", + "0 * np.nan\n", + "np.nan == np.nan\n", + "np.inf > np.nan\n", + "np.nan - np.nan\n", + "0.3 == 3 * 0.1\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 18. Create a 5x5 matrix with values 1,2,3,4 just below the diagonal (★☆☆) \n", + "(**hint**: np.diag)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 19. Create a 8x8 matrix and fill it with a checkerboard pattern (★☆☆) \n", + "(**hint**: array\\[::2\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 20. Consider a (6,7,8) shape array, what is the index (x,y,z) of the 100th element? \n", + "(**hint**: np.unravel_index)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆) \n", + "(**hint**: np.tile)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 22. Normalize a 5x5 random matrix (★☆☆) \n", + "(**hint**: (x - min) / (max - min))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 23. Create a custom dtype that describes a color as four unsigned bytes (RGBA) (★☆☆) \n", + "(**hint**: np.dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 24. Multiply a 5x3 matrix by a 3x2 matrix (real matrix product) (★☆☆) \n", + "(**hint**: np.dot | @)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 25. Given a 1D array, negate all elements which are between 3 and 8, in place. (★☆☆) \n", + "(**hint**: >, <=)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 26. What is the output of the following script? (★☆☆) \n", + "(**hint**: np.sum)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```python\n", + "# Author: Jake VanderPlas\n", + "\n", + "print(sum(range(5),-1))\n", + "from numpy import *\n", + "print(sum(range(5),-1))\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 27. Consider an integer vector Z, which of these expressions are legal? (★☆☆)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```python\n", + "Z**Z\n", + "2 << Z >> 2\n", + "Z <- Z\n", + "1j*Z\n", + "Z/1/1\n", + "ZZ\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 28. What are the result of the following expressions?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```python\n", + "np.array(0) / np.array(0)\n", + "np.array(0) // np.array(0)\n", + "np.array([np.nan]).astype(int).astype(float)\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 29. How to round away from zero a float array ? (★☆☆) \n", + "(**hint**: np.uniform, np.copysign, np.ceil, np.abs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 30. How to find common values between two arrays? (★☆☆) \n", + "(**hint**: np.intersect1d)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) \n", + "(**hint**: np.seterr, np.errstate)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 32. Is the following expressions true? (★☆☆) \n", + "(**hint**: imaginary number)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```python\n", + "np.sqrt(-1) == np.emath.sqrt(-1)\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 33. How to get the dates of yesterday, today and tomorrow? (★☆☆) \n", + "(**hint**: np.datetime64, np.timedelta64)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 34. How to get all the dates corresponding to the month of July 2016? (★★☆) \n", + "(**hint**: np.arange(dtype=datetime64\\['D'\\]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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=))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 36. Extract the integer part of a random array using 5 different methods (★★☆) \n", + "(**hint**: %, np.floor, np.ceil, astype, np.trunc)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 37. Create a 5x5 matrix with row values ranging from 0 to 4 (★★☆) \n", + "(**hint**: np.arange)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 38. Consider a generator function that generates 10 integers and use it to build an array (★☆☆) \n", + "(**hint**: np.fromiter)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆) \n", + "(**hint**: np.linespace)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 40. Create a random vector of size 10 and sort it (★★☆) \n", + "(**hint**: sort)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 41. How to sum a small array faster than np.sum? (★★☆) \n", + "(**hint**: np.add.reduce)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 42. Consider two random array A and B, check if they are equal (★★☆) \n", + "(**hint**: np.allclose, np.array\\_equal)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 43. Make an array immutable (read-only) (★★☆) \n", + "(**hint**: flags.writeable)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 44. Consider a random 10x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆) \n", + "(**hint**: np.sqrt, np.arctan2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 45. Create random vector of size 10 and replace the maximum value by 0 (★★☆) \n", + "(**hint**: argmax)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 46. Create a structured array with `x` and `y` coordinates covering the \\[0,1\\]x\\[0,1\\] area (★★☆) \n", + "(**hint**: np.meshgrid)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 47. Given two arrays, X and Y, construct the Cauchy matrix C (Cij =1/(xi - yj)) \n", + "(**hint**: np.subtract.outer)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 48. Print the minimum and maximum representable value for each numpy scalar type (★★☆) \n", + "(**hint**: np.iinfo, np.finfo, eps)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 49. How to print all the values of an array? (★★☆) \n", + "(**hint**: np.set\\_printoptions)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 50. How to find the closest value (to a given scalar) in a vector? (★★☆) \n", + "(**hint**: argmin)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 51. Create a structured array representing a position (x,y) and a color (r,g,b) (★★☆) \n", + "(**hint**: dtype)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 52. Consider a random vector with shape (100,2) representing coordinates, find point by point distances (★★☆) \n", + "(**hint**: np.atleast\\_2d, T, np.sqrt)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place? \n", + "(**hint**: astype(copy=False))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 54. How to read the following file? (★★☆) \n", + "(**hint**: np.genfromtxt)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "1, 2, 3, 4, 5\n", + "6, , , 7, 8\n", + " , , 9,10,11\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆) \n", + "(**hint**: np.ndenumerate, np.ndindex)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 56. Generate a generic 2D Gaussian-like array (★★☆) \n", + "(**hint**: np.meshgrid, np.exp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 57. How to randomly place p elements in a 2D array? (★★☆) \n", + "(**hint**: np.put, np.random.choice)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 58. Subtract the mean of each row of a matrix (★★☆) \n", + "(**hint**: mean(axis=,keepdims=))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 59. How to sort an array by the nth column? (★★☆) \n", + "(**hint**: argsort)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 60. How to tell if a given 2D array has null columns? (★★☆) \n", + "(**hint**: any, ~)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 61. Find the nearest value from a given value in an array (★★☆) \n", + "(**hint**: np.abs, argmin, flat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆) \n", + "(**hint**: np.nditer)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 63. Create an array class that has a name attribute (★★☆) \n", + "(**hint**: class method)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 65. How to accumulate elements of a vector (X) to an array (F) based on an index list (I)? (★★★) \n", + "(**hint**: np.bincount)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 66. Considering a (w,h,3) image of (dtype=ubyte), compute the number of unique colors (★★★) \n", + "(**hint**: np.unique)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 67. Considering a four dimensions array, how to get sum over the last two axis at once? (★★★) \n", + "(**hint**: sum(axis=(-2,-1)))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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? (★★★) \n", + "(**hint**: np.bincount)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 69. How to get the diagonal of a dot product? (★★★) \n", + "(**hint**: np.diag)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 71. Consider an array of dimension (5,5,3), how to mulitply it by an array with dimensions (5,5)? (★★★) \n", + "(**hint**: array\\[:, :, None\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 72. How to swap two rows of an array? (★★★) \n", + "(**hint**: array\\[\\[\\]\\] = array\\[\\[\\]\\])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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 (★★★) \n", + "(**hint**: repeat, np.roll, np.sort, view, np.unique)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 75. How to compute averages using a sliding window over an array? (★★★) \n", + "(**hint**: np.cumsum)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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\\]) (★★★) \n", + "(**hint**: from numpy.lib import stride_tricks)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 77. How to negate a boolean, or to change the sign of a float inplace? (★★★) \n", + "(**hint**: np.logical_not, np.negative)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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\\])? (★★★)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 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\\])? (★★★)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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) (★★★) \n", + "(**hint**: minimum, maximum)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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\\]\\]? (★★★) \n", + "(**hint**: stride\\_tricks.as\\_strided)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 82. Compute a matrix rank (★★★) \n", + "(**hint**: np.linalg.svd) (suggestion: np.linalg.svd)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 83. How to find the most frequent value in an array? \n", + "(**hint**: np.bincount, argmax)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 84. Extract all the contiguous 3x3 blocks from a random 10x10 matrix (★★★) \n", + "(**hint**: stride\\_tricks.as\\_strided)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 85. Create a 2D array subclass such that Z\\[i,j\\] == Z\\[j,i\\] (★★★) \n", + "(**hint**: class method)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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)) (★★★) \n", + "(**hint**: np.tensordot)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) \n", + "(**hint**: np.add.reduceat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 88. How to implement the Game of Life using numpy arrays? (★★★)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 89. How to get the n largest values of an array (★★★) \n", + "(**hint**: np.argsort | np.argpartition)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 90. Given an arbitrary number of vectors, build the cartesian product (every combinations of every item) (★★★) \n", + "(**hint**: np.indices)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 91. How to create a record array from a regular array? (★★★) \n", + "(**hint**: np.core.records.fromarrays)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 92. Consider a large vector Z, compute Z to the power of 3 using 3 different methods (★★★) \n", + "(**hint**: np.power, \\*, np.einsum)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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? (★★★) \n", + "(**hint**: np.where)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 94. Considering a 10x3 matrix, extract rows with unequal values (e.g. \\[2,2,3\\]) (★★★)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 95. Convert a vector of ints into a matrix binary representation (★★★) \n", + "(**hint**: np.unpackbits)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 96. Given a two dimensional array, how to extract unique rows? (★★★) \n", + "(**hint**: np.ascontiguousarray)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★) \n", + "(**hint**: np.einsum)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### 98. Considering a path described by two vectors (X,Y), how to sample it using equidistant samples (★★★)? \n", + "(**hint**: np.cumsum, np.interp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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. (★★★) \n", + "(**hint**: np.logical\\_and.reduce, np.mod)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "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). (★★★) \n", + "(**hint**: np.percentile)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.0" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/100 Numpy exercises with hint.md b/100 Numpy exercises with hint.md new file mode 100644 index 0000000..1bfc5d1 --- /dev/null +++ b/100 Numpy exercises with hint.md @@ -0,0 +1,633 @@ + +# 100 numpy exercises with hint + +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 +to reach the 100 limit. 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. + +If you find an error or think you've a better way to solve some of them, feel +free to open an issue at + +#### 1. Import the numpy package under the name `np` (★☆☆) + +(**hint**: import … as …) + + + +#### 2. Print the numpy version and the configuration (★☆☆) + +(**hint**: np.\_\_verison\_\_, 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**: np.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 0's) around an existing array? (★☆☆) + +(**hint**: np.pad) + + + +#### 17. What is the result of the following expression? (★☆☆) + +(**hint**: NaN = not a number, inf = infinity) + + +```python +0 * np.nan +np.nan == np.nan +np.inf > np.nan +np.nan - np.nan +0.3 == 3 * 0.1 +``` + +#### 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 - min) / (max - min)) + + + +#### 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**: np.dot | @) + + + +#### 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? (★☆☆) + +(**hint**: np.sum) + + +```python +# Author: Jake VanderPlas + +print(sum(range(5),-1)) +from numpy import * +print(sum(range(5),-1)) +``` + +#### 27. Consider an integer vector Z, which of these expressions are legal? (★☆☆) + + +```python +Z**Z +2 << Z >> 2 +Z <- Z +1j*Z +Z/1/1 +ZZ +``` + +#### 28. What are the result of the following expressions? + + +```python +np.array(0) / np.array(0) +np.array(0) // np.array(0) +np.array([np.nan]).astype(int).astype(float) +``` + +#### 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? (★☆☆) + +(**hint**: np.intersect1d) + + + +#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆) + +(**hint**: np.seterr, np.errstate) + + + +#### 32. Is the following expressions true? (★☆☆) + +(**hint**: imaginary number) + + +```python +np.sqrt(-1) == np.emath.sqrt(-1) +``` + +#### 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 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 (★★☆) + +(**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.linespace) + + + +#### 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**: astype(copy=False)) + + + +#### 54. How to read the following file? (★★☆) + +(**hint**: np.genfromtxt) + + +``` +1, 2, 3, 4, 5 +6, , , 7, 8 + , , 9,10,11 +``` + +#### 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 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) + + + +#### 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\[i\])? (★★★) + + + +#### 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\[i\])? (★★★) + + + +#### 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) + + + +#### 82. Compute a matrix rank (★★★) + +(**hint**: np.linalg.svd) + + + +#### 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) + + + +#### 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)) (★★★) + +(**hint**: np.tensordot) + + + +#### 87. Consider a 16x16 array, how to get the block-sum (block size is 4x4)? (★★★) + +(**hint**: np.add.reduceat) + + + +#### 88. How to implement the Game of Life using numpy arrays? (★★★) + + + +#### 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. \[2,2,3\]) (★★★) + + + +#### 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) + + + +#### 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) +