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+{"cells":[{"cell_type":"markdown","metadata":{},"source":["1. Import the NUMPY package under the name np."]},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[],"source":["import numpy as np"]},{"cell_type":"markdown","metadata":{},"source":["2. Print the NUMPY version and the configuration."]},{"cell_type":"code","execution_count":4,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["1.26.1\n"]}],"source":["print(np.__version__)"]},{"cell_type":"markdown","metadata":{},"source":["3. Generate a 2x3x5 3-dimensional array with random values. Assign the array to variable \"a\"<br>\n","Challenge: there are at least three easy ways that use numpy to generate random arrays. How many ways can you find?"]},{"cell_type":"code","execution_count":5,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["[[[11 17 14 37 65]\n","  [44 67 52 45 52]\n","  [86 47 91  1 49]]\n","\n"," [[69 99 54 97 90]\n","  [90 19 33 70 26]\n","  [92 80 11 94 24]]]\n","<class 'numpy.ndarray'>\n"]}],"source":["# 1. We with randit\n","a = np.random.randint(100,size=(2,3,5))\n","print(a)\n","print(type(a))\n"]},{"cell_type":"markdown","metadata":{},"source":["4. Print a."]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["[[[11 17 14 37 65]\n","  [44 67 52 45 52]\n","  [86 47 91  1 49]]\n","\n"," [[69 99 54 97 90]\n","  [90 19 33 70 26]\n","  [92 80 11 94 24]]]\n"]}],"source":["print(a)"]},{"cell_type":"markdown","metadata":{},"source":["5. Create a 5x2x3 3-dimensional array with all values equaling 1.<br>\n","ssign the array to variable \"b\""]},{"cell_type":"code","execution_count":7,"metadata":{},"outputs":[],"source":["b = np.ones((5,2,3), dtype= int)"]},{"cell_type":"markdown","metadata":{},"source":["6. Print b."]},{"cell_type":"code","execution_count":8,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["[[[1 1 1]\n","  [1 1 1]]\n","\n"," [[1 1 1]\n","  [1 1 1]]\n","\n"," [[1 1 1]\n","  [1 1 1]]\n","\n"," [[1 1 1]\n","  [1 1 1]]\n","\n"," [[1 1 1]\n","  [1 1 1]]]\n"]}],"source":["print(b)"]},{"cell_type":"markdown","metadata":{},"source":["7. Do a and b have the same size? How do you prove that in Python code?"]},{"cell_type":"markdown","metadata":{},"source":["Yes they have the same size"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["30 30\n"]}],"source":["print(np.size(a), np.size(b))"]},{"cell_type":"markdown","metadata":{},"source":["8. Are you able to add a and b? Why or why not?"]},{"cell_type":"markdown","metadata":{},"source":["We can't because they different dimension"]},{"cell_type":"code","execution_count":10,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["(2, 3, 5) (5, 2, 3)\n"]}],"source":["print(a.shape, b.shape)"]},{"cell_type":"code","execution_count":11,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["The 2 arrays have diffent shape\n"]}],"source":["try:\n","    sum(a,b)\n","except:\n","    print(\"The 2 arrays have diffent shape\")"]},{"cell_type":"markdown","metadata":{},"source":["9. Transpose b so that it has the same structure of a (i.e. become a 2x3x5 array). Assign the transposed array to varialbe \"c\"."]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["(2, 3, 5)\n","[[[1 1 1 1 1]\n","  [1 1 1 1 1]\n","  [1 1 1 1 1]]\n","\n"," [[1 1 1 1 1]\n","  [1 1 1 1 1]\n","  [1 1 1 1 1]]]\n"]}],"source":["c = b.transpose(1,2,0)\n","print(c.shape)\n","print(c)"]},{"cell_type":"markdown","metadata":{},"source":["10. Try to add a and c. Now it should work. Assign the sum to varialbe \"d\". But why does it work now?"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[],"source":["d = c + a"]},{"cell_type":"markdown","metadata":{},"source":["11. Print a and d. Notice the difference and relation of the two array in terms of the values? Explain."]},{"cell_type":"code","execution_count":14,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["[[[ 12  18  15  38  66]\n","  [ 45  68  53  46  53]\n","  [ 87  48  92   2  50]]\n","\n"," [[ 70 100  55  98  91]\n","  [ 91  20  34  71  27]\n","  [ 93  81  12  95  25]]]\n"]}],"source":["\n","print(d)\n"]},{"cell_type":"markdown","metadata":{},"source":["12. Multiply a and c. Assign the result to e."]},{"cell_type":"code","execution_count":15,"metadata":{},"outputs":[{"data":{"text/plain":["array([[[11, 17, 14, 37, 65],\n","        [44, 67, 52, 45, 52],\n","        [86, 47, 91,  1, 49]],\n","\n","       [[69, 99, 54, 97, 90],\n","        [90, 19, 33, 70, 26],\n","        [92, 80, 11, 94, 24]]])"]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["e = a * c\n","e"]},{"cell_type":"markdown","metadata":{},"source":["13. Does e equal to a? Why or why not?"]},{"cell_type":"markdown","metadata":{},"source":["The result is equal to A because we're doing the procut with an Array compose of ones. We are able to do the product of both ARRAYS because they have the same shape."]},{"cell_type":"markdown","metadata":{},"source":["14. Identify the max, min, and mean values in d. Assign those values to variables \"d_max\", \"d_min\", and \"d_mean\""]},{"cell_type":"code","execution_count":16,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["100 2 55.2\n"]}],"source":["d_max = np.max(d)\n","d_min = np.min(d)\n","d_mean = np.mean(d)\n","print(d_max, d_min,d_mean)"]},{"cell_type":"markdown","metadata":{},"source":["15. Now we want to label the values in d. First create an empty array \"f\" with the same shape (i.e. 2x3x5) as d using `np.empty`."]},{"cell_type":"code","execution_count":33,"metadata":{},"outputs":[],"source":["f = np.empty((2,3,5))"]},{"cell_type":"markdown","metadata":{},"source":["\n","16. Populate the values in f. For each value in d, if it's larger than d_min but smaller than d_mean, assign 25 to the corresponding value in f.<br>\n","If a value in d is larger than d_mean but smaller than d_max, assign 75 to the corresponding value in f.<br>\n","If a value equals to d_mean, assign 50 to the corresponding value in f.<br>\n","Assign 0 to the corresponding value(s) in f for d_min in d.<br>\n","Assign 100 to the corresponding value(s) in f for d_max in d.<br>\n","In the end, f should have only the following values: 0, 25, 50, 75, and 100.<br>\n","Note: you don't have to use Numpy in this question.<br>\n"]},{"cell_type":"code","execution_count":34,"metadata":{},"outputs":[],"source":["for i in range(2):\n","    for j in range(3):\n","        for k in range(5):\n","            if d[i][j][k] > d_min and d[i][j][k] < d_mean:\n","                f[i][j][k] = 25\n","            if d[i][j][k] > d_mean:\n","                f[i][j][k] = 5\n","            if d[i][j][k] == d_mean:\n","                f[i][j][k] = 50 \n","            if d[i][j][k] == d_min:\n","                f[i][j][k] = 0                 \n","            elif d[i][j][k] == d_max:\n","                f[i][j][k] = 100\n"]},{"cell_type":"code","execution_count":35,"metadata":{},"outputs":[{"ename":"TypeError","evalue":"'numpy.ndarray' object is not callable","output_type":"error","traceback":["\u001b[1;31m---------------------------------------------------------------------------\u001b[0m","\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)","\u001b[1;32mc:\\Users\\enamo\\Documents\\Ironhack\\labs\\lab-numpy\\your-code\\main.ipynb Cell 36\u001b[0m line \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/enamo/Documents/Ironhack/labs/lab-numpy/your-code/main.ipynb#X50sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mprint\u001b[39m(f)\n","\u001b[1;31mTypeError\u001b[0m: 'numpy.ndarray' object is not callable"]}],"source":["print(f)"]},{"cell_type":"markdown","metadata":{},"source":["17. Print d and f. Do you have your expected f?<br>\n","For instance, if your d is:<br>\n","array([[[1.85836099, 1.67064465, 1.62576044, 1.40243961, 1.88454931],<br>\n","        [1.75354326, 1.69403643, 1.36729252, 1.61415071, 1.12104981],<br>\n","        [1.72201435, 1.1862918 , 1.87078449, 1.7726778 , 1.88180042]],<br>\n","       [[1.44747908, 1.31673383, 1.02000951, 1.52218947, 1.97066381],<br>\n","        [1.79129243, 1.74983003, 1.96028037, 1.85166831, 1.65450881],<br>\n","        [1.18068344, 1.9587381 , 1.00656599, 1.93402165, 1.73514584]]])<br>\n","Your f should be:<br>\n","array([[[ 75.,  75.,  75.,  25.,  75.],<br>\n","        [ 75.,  75.,  25.,  25.,  25.],<br>\n","        [ 75.,  25.,  75.,  75.,  75.]],<br>\n","       [[ 25.,  25.,  25.,  25., 100.],<br>\n","        [ 75.,  75.,  75.,  75.,  75.],<br>\n","        [ 25.,  75.,   0.,  75.,  75.]]])<br>\n"]},{"cell_type":"markdown","metadata":{},"source":["\n","<br>\n","#18. Bonus question: instead of using numbers (i.e. 0, 25, 50, 75, and 100), how to use string values <br>\n","(\"A\", \"B\", \"C\", \"D\", and \"E\") to label the array elements? You are expecting the result to be:<br>\n","array([[[ 'D',  'D',  'D',  'B',  'D'],<br>\n","        [ 'D',  'D',  'B',  'B',  'B'],<br>\n","        [ 'D',  'B',  'D',  'D',  'D']],<br>\n","       [[ 'B',  'B',  'B',  'B',  'E'],<br>\n","        [ 'D',  'D',  'D',  'D',  'D'],<br>\n","        [ 'B',  'D',   'A',  'D', 'D']]])<br>\n","Again, you don't need Numpy in this question.<br>\n"]}],"metadata":{"kernelspec":{"display_name":"ironhack","language":"python","name":"ironhack"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.5"}},"nbformat":4,"nbformat_minor":2}