Python_Numpy_Exercises_with_hints.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "bf79c78b",
   "metadata": {},
   "source": [
    "# Python NumPy Exercises\n",
    "\n",
    "This is a collection of exercises that have been collected in the numpy mailing list, on stack overflow\n",
    "and in the numpy documentation. The goal of this collection is to offer a quick reference for both old\n",
    "and new users but also to provide a set of exercises for those who teach."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "017db353",
   "metadata": {},
   "source": [
    "#### 1. Import the numpy package under the name `np` and print the numpy version and the configuration (★☆☆)\n",
    "\n",
    "`Hint: import … as` and `np.__version__, np.show_config)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e28779fe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "46950f4f",
   "metadata": {},
   "source": [
    "#### 2. Convert a list of numeric value into a one-dimensional NumPy array (★☆☆)\n",
    "`💡 hint: numpy.array`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b0e875f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e3c20b3d",
   "metadata": {},
   "source": [
    "#### 3. Create a null vector of size 9 (★☆☆)\n",
    "`💡 hint: np.zeros`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96d0b63e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b15a879f",
   "metadata": {},
   "source": [
    "#### 4. How to find the memory size of any array (★☆☆)\n",
    "`💡 hint: size, itemsize`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32f9025c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0a708990",
   "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,
   "id": "d254eea5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0b16cd77",
   "metadata": {},
   "source": [
    "#### 6. Create a null vector of size 12 but the sixth value which is 1 (★☆☆)\n",
    "`💡hint: array[12]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05223560",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "782d4c77",
   "metadata": {},
   "source": [
    "#### 7. Create a vector with values ranging from 20 to 59 (★☆☆)\n",
    "`💡hint: arange`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7250d114",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "48d48f01",
   "metadata": {},
   "source": [
    "#### 8. Reverse a vector (first element becomes last) (★☆☆)\n",
    "`💡hint: array[::-1]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fb702ae0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4fa39382",
   "metadata": {},
   "source": [
    "#### 9. Create a 3x3 matrix with values ranging from 12 to 20 (★☆☆)\n",
    "`💡hint: reshape`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97e6be92",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "da64551a",
   "metadata": {},
   "source": [
    "#### 10. Find indices of non-zero elements from [3,7,0,0,9,0] (★☆☆)\n",
    "`💡hint: np.nonzero`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "322b2b68",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f89d9c9e",
   "metadata": {},
   "source": [
    "#### 11. Create a 4x4 identity matrix (★☆☆)\n",
    "`💡hint: np.eye`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5717e1c1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7e44c6fa",
   "metadata": {},
   "source": [
    "#### 12. Create a 2x2x2 array with random values (★☆☆)\n",
    "`💡hint: np.random.random`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8fd52e1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "13c5928c",
   "metadata": {},
   "source": [
    "#### 13. Create a 9x9 array with random values and find the minimum and maximum values (★☆☆)\n",
    "`💡hint: min, max`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0ede4d26",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3fa2e461",
   "metadata": {},
   "source": [
    "#### 14. Create a random vector of size 20 and find the mean value (★☆☆)\n",
    "`💡hint: mean`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0048e59",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "73f7a549",
   "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,
   "id": "351ff928",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6d0c506f",
   "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,
   "id": "c1cc1143",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d6ad1a9f",
   "metadata": {},
   "source": [
    "#### 17. What is the result of the following expression? (★☆☆)\n",
    "```python\n",
    "0 * np.nan\n",
    "np.nan == np.nan\n",
    "np.inf > np.nan\n",
    "np.nan - np.nan\n",
    "np.nan in set([np.nan])\n",
    "0.7 == 7 * 0.1\n",
    "```\n",
    "`💡hint: NaN = not a number, inf = infinity`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ba3c441",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e3a7ba7f",
   "metadata": {},
   "source": [
    "#### 18. Create a 6x6 matrix with values 1,2,3,4 just below the diagonal (★☆☆)\n",
    "`💡hint: np.diag`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b874734e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6d17ab5d",
   "metadata": {},
   "source": [
    "#### 19. Create a 6x6 matrix and fill it with a checkerboard pattern (★☆☆)\n",
    "`💡hint: array[::2]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c4e2c5e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8837119b",
   "metadata": {},
   "source": [
    "#### 20. Consider a (8,9,10) shape array, what is the index (x,y,z) of the 100th element? (★☆☆)\n",
    "`💡hint: np.unravel_index`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b05c544",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ec788c9f",
   "metadata": {},
   "source": [
    "#### 21. Create a checkerboard 8x8 matrix using the tile function (★☆☆)\n",
    "`💡hint: np.tile`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3980b2c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "391791e0",
   "metadata": {},
   "source": [
    "#### 22. Normalize a 6x6 random matrix (★☆☆)\n",
    "`💡hint: (x -mean)/std`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ada71c06",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1e74d39e",
   "metadata": {},
   "source": [
    "#### 23. find the number of elements of an array, length of one array element in bytes and total bytes consumed by the elements. (★☆☆)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb0e066c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "78250c14",
   "metadata": {},
   "source": [
    "#### 24. Multiply a 6x3 matrix by a 3x4 matrix (real matrix product) (★☆☆)\n",
    "`💡hint: np.dot` or `np.ones`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e482afe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "51898680",
   "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,
   "id": "ee92ccaf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "89e78048",
   "metadata": {},
   "source": [
    "#### 26. What is the output of the following script? (★☆☆)\n",
    "```python\n",
    "\n",
    "print(sum(range(5),-1))\n",
    "from numpy import *\n",
    "print(sum(range(5),-1))\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8026c969",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ebd10810",
   "metadata": {},
   "source": [
    "#### 27. Write a Python program compare two arrays using numpy (★☆☆)\n",
    "```python\n",
    "Array a: [1 2]\n",
    "Array b: [4 5]\n",
    "a > b \n",
    "[False False]\n",
    "a >= b \n",
    "[False False] \n",
    "a < b \n",
    "[ True True] \n",
    "a <= b \n",
    "[ True True]\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90fed5c6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c0e940f8",
   "metadata": {},
   "source": [
    "#### 28. What are the result of the following expressions? (★☆☆)\n",
    "```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",
    "```\n",
    "Consider an integer vector a\n",
    "```python\n",
    "a**a\n",
    "a << a >> 2\n",
    "a <- a\n",
    "1j*a\n",
    "a/1/1\n",
    "a<a>a\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50d84cdf",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "22713c3f",
   "metadata": {},
   "source": [
    "#### 29. How to round away from zero a float array ? (★☆☆)\n",
    "`💡hint: np.uniform, np.copysign, np.ceil, np.abs, np.where`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85ebdda9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f1ae2c2d",
   "metadata": {},
   "source": [
    "#### 30. How to find common values between two arrays? (★☆☆)\n",
    "`💡hint: np.intersect1d`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "097482ad",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "34a7bdee",
   "metadata": {},
   "source": [
    "#### 31. How to ignore all numpy warnings (not recommended)? (★☆☆)\n",
    "`💡hint: np.seterr, np.errstate`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95ba8c7d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "37bc0973",
   "metadata": {},
   "source": [
    "#### 32. Is the following expressions true? (★☆☆)\n",
    "```python\n",
    "np.sqrt(-1) == np.emath.sqrt(-1)\n",
    "```\n",
    "`💡hint: imaginary number`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6925e9db",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "129c342d",
   "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,
   "id": "0fd2f947",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "42f8b2f9",
   "metadata": {},
   "source": [
    "#### 34. How to get all the dates corresponding to the month of January 2016? (★★☆)\n",
    "`💡hint: np.arange(dtype=datetime64['D'])`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ad086b0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "252c43e2",
   "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,
   "id": "34488d4b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "486df8ea",
   "metadata": {},
   "source": [
    "#### 36. Extract the integer part of a random array of positive numbers using 4 different methods (★★☆)\n",
    "`💡hint: %, np.floor, astype, np.trunc`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2680c1ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "649e89f9",
   "metadata": {},
   "source": [
    "#### 37. Create a 3x3 matrix with row values ranging from 0 to 2 (★★☆)\n",
    "`💡hint: np.arange`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e832212f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3421e17f",
   "metadata": {},
   "source": [
    "#### 38. Consider a generator function that generates 9 integers and use it to build an array (★☆☆)\n",
    "`💡hint: np.fromiter`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d97fcb71",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "483dd554",
   "metadata": {},
   "source": [
    "#### 39. Create a vector of size 10 with values ranging from 0 to 1, both excluded (★★☆)\n",
    "`💡hint: np.linspace`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "572668cb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2d07be1c",
   "metadata": {},
   "source": [
    "#### 40. Create a random vector of size 10 and sort it (★★☆)\n",
    "`💡hint: sort`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "046a541a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6415f02e",
   "metadata": {},
   "source": [
    "#### 41. How to sum a small array faster than np.sum? (★★☆)\n",
    "`💡hint: np.add.reduce`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "129e785f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "fe043549",
   "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,
   "id": "7ada2e2b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cc08f71c",
   "metadata": {},
   "source": [
    "#### 43. Make an array immutable (read-only) (★★☆)\n",
    "`💡hint: flags.writeable`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b91afd1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2002cb03",
   "metadata": {},
   "source": [
    "#### 44. Consider a random 5x2 matrix representing cartesian coordinates, convert them to polar coordinates (★★☆)\n",
    "`💡hint: np.sqrt, np.arctan2`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16476671",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b7109c9f",
   "metadata": {},
   "source": [
    "#### 45. Create random vector of size 5 and replace the maximum value by 0 (★★☆)\n",
    "`💡hint: argmax`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89b75e6d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7d3131b9",
   "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,
   "id": "445532d0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7c8c1fc5",
   "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,
   "id": "7668afae",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5795b4bd",
   "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,
   "id": "f2eaddaa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "fb24674c",
   "metadata": {},
   "source": [
    "#### 49. How to print all the values of an array? (★★☆)\n",
    "`💡hint: np.set_printoptions`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bdfaefe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e6e1ae2f",
   "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,
   "id": "29a9e416",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c01f0ecf",
   "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,
   "id": "a3241eca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3b64a18b",
   "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,
   "id": "f27585c3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "48413134",
   "metadata": {},
   "source": [
    "#### 53. How to convert a float (32 bits) array into an integer (32 bits) in place?\n",
    "`💡hint: view and [:] =`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59c8357d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0a532633",
   "metadata": {},
   "source": [
    "#### 54. How to read the following file? (★★☆)\n",
    "```\n",
    "1, 2, 3, 4, 5\n",
    "6,  ,  , 7, 8\n",
    " ,  , 9,10,11\n",
    "```\n",
    "`💡hint: np.genfromtxt`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81b2915b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f98713a6",
   "metadata": {},
   "source": [
    "#### 55. What is the equivalent of enumerate for numpy arrays? (★★☆)\n",
    "`💡hint: np.ndenumerate, np.ndindex`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c8ace8dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1abc7cc8",
   "metadata": {},
   "source": [
    "#### 56. Generate a generic 2D Gaussian-like array (★★☆)\n",
    "`💡hint: np.meshgrid, np.exp`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8389dbf6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0cf413ee",
   "metadata": {},
   "source": [
    "#### 57. How to randomly place e elements in a 2D array? (★★☆)\n",
    "`💡hint: np.put, np.random.choice`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "884c88de",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "215b6acc",
   "metadata": {},
   "source": [
    "#### 58. Subtract the mean of each row of a matrix (★★☆)\n",
    "`💡hint: mean(axis=,keepdims=)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76d3b16a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c0cf37e0",
   "metadata": {},
   "source": [
    "#### 59. How to sort an array by the nth column? (★★☆)\n",
    "`💡hint: argsort`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f99dfd2a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c17fb213",
   "metadata": {},
   "source": [
    "#### 60. How to tell if a given 2D array has null columns? (★★☆)\n",
    "`💡hint: any, ~`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84346fc8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8aaab886",
   "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,
   "id": "72a6090d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "66a04e2e",
   "metadata": {},
   "source": [
    "#### 62. Considering two arrays with shape (1,3) and (3,1), how to compute their sum using an iterator? (★★☆)\n",
    "`💡"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "93774f24",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f4427f7f",
   "metadata": {},
   "source": [
    "#### 63. Create an array class that has a name attribute (★★☆)\n",
    "`💡hint: class method`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e1952ed",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "58be9dd4",
   "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,
   "id": "9cf9e134",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7348abd0",
   "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,
   "id": "43a58dde",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "538e651c",
   "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,
   "id": "60b487a1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "33c986d9",
   "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,
   "id": "6ba943fe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "00eb27c4",
   "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,
   "id": "177b219c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "928a1a15",
   "metadata": {},
   "source": [
    "#### 69. How to get the diagonal of a dot product? (★★★)\n",
    "`💡hint: np.diag`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "038b9c1c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5143f7f3",
   "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,
   "id": "9913e7b0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f62551d8",
   "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,
   "id": "02967528",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6896e326",
   "metadata": {},
   "source": [
    "#### 72. How to swap two rows of an array? (★★★)\n",
    "`💡hint: array[[]] = array[[]]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33488c53",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "aeaf4a7b",
   "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,
   "id": "be837a66",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "3d11451b",
   "metadata": {},
   "source": [
    "#### 74. Given a sorted array C that corresponds to a bincount, how to produce an array A such that np.bincount(A) == C? (★★★)\n",
    "`💡hint: np.repeat`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6912341a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a0a45995",
   "metadata": {},
   "source": [
    "#### 75. How to compute averages using a sliding window over an array? (★★★)\n",
    "`💡hint: np.cumsum`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d307be78",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7808578f",
   "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,
   "id": "539e5596",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8e83df46",
   "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,
   "id": "90da18ec",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e67ff31c",
   "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,
   "id": "aaa0c5cb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ad8821b1",
   "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,
   "id": "12f9a524",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a0c8cbf5",
   "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,
   "id": "6e44ae96",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "781fa236",
   "metadata": {},
   "source": [
    "#### 81. Consider an array a = [1,2,3,4,5,6,7,8,9,10,11,12,13,14], how to generate an array b = [[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,
   "id": "82e3d17e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "9c9bb0f3",
   "metadata": {},
   "source": [
    "#### 82. Compute a matrix rank (★★★)\n",
    "`💡hint: np.linalg.svd`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18f053fa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7d8dc135",
   "metadata": {},
   "source": [
    "#### 83. How to find the most frequent value in an array?\n",
    "`💡hint: np.bincount, argmax`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81844e99",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "aa340126",
   "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,
   "id": "f39dd2dd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6b6d2c84",
   "metadata": {},
   "source": [
    "#### 85. Create a 2D array subclass such that a[i,j] == a[j,i] (★★★)\n",
    "`💡hint: class method`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1916d67d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7be0fe36",
   "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,
   "id": "1d07c08f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a840a88f",
   "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,
   "id": "7200f861",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c2bd7385",
   "metadata": {},
   "source": [
    "#### 88. How to implement the Game of Life using numpy arrays? (★★★)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a5d67d2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "4c70397b",
   "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,
   "id": "732993b7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "15ba193c",
   "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,
   "id": "3a315a00",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ec828405",
   "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,
   "id": "608a017a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "d94352b6",
   "metadata": {},
   "source": [
    "#### 92. Consider a large vector A, compute A to the power of 3 using 3 different methods (★★★)\n",
    "`💡hint: np.power, *, np.einsum`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "759d5ce5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "7c3a9e32",
   "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,
   "id": "5c293501",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "da9d5eeb",
   "metadata": {},
   "source": [
    "#### 94. Considering a 10x3 matrix, extract rows with unequal values (e.g. [2,2,3]) (★★★)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "89d5fba0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f7b65fd5",
   "metadata": {},
   "source": [
    "#### 95. Convert a vector of ints into a matrix binary representation (★★★)\n",
    "`💡hint: np.unpackbits`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4edef8b1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2784c996",
   "metadata": {},
   "source": [
    "#### 96. Given a two dimensional array, how to extract unique rows? (★★★)\n",
    "`💡hint: np.ascontiguousarray | np.unique`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d65d01e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "71a7574c",
   "metadata": {},
   "source": [
    "#### 97. Considering 2 vectors A & B, write the einsum equivalent of inner, outer, sum, and mul function (★★★)\n",
    "`💡hint: np.einsum`"
   ]
  },
  {
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   "execution_count": null,
   "id": "43471b2e",
   "metadata": {},
   "outputs": [],
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   "id": "30f06441",
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   "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,
   "id": "ddac593f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "e5737276",
   "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,
   "id": "5d0d0fa8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5882e36d",
   "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,
   "id": "c21a8816",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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