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| 1 | +import numpy as np |
| 2 | + |
| 3 | +pip install numpy |
| 4 | +pip install numpy --upgrade |
| 5 | + |
| 6 | +import numpy as np |
| 7 | + |
| 8 | +a = np.array([2,3,4]) |
| 9 | + |
| 10 | +a = np.arange(1, 12, 2) # (from, to, step) |
| 11 | + |
| 12 | +a = np.linspace(1, 12, 6) # (first, last, num_elements) float data type |
| 13 | + |
| 14 | +a.reshape(3,2) |
| 15 | +a = a.reshape(3,2) |
| 16 | + |
| 17 | +a.size |
| 18 | + |
| 19 | +a.shape |
| 20 | + |
| 21 | +a.dtype |
| 22 | + |
| 23 | +a.itemsize |
| 24 | + |
| 25 | +# this works: |
| 26 | +b = np.array([(1.5,2,3), (4,5,6)]) |
| 27 | + |
| 28 | +# but this does not work: |
| 29 | +b = np.array(1,2,3) # square brackets are required |
| 30 | + |
| 31 | +a < 4 # prints True/False |
| 32 | + |
| 33 | +a * 3 # multiplies each element by 3 |
| 34 | +a *= 3 # saves result to a |
| 35 | + |
| 36 | +a = np.zeros((3,4)) |
| 37 | + |
| 38 | +a = np.ones((2,3)) |
| 39 | + |
| 40 | +a = np.array([2,3,4], dtype=np.int16) |
| 41 | + |
| 42 | +a = np.random.random((2,3)) |
| 43 | + |
| 44 | +np.set_printoptions(precision=2, suppress=True) # show 2 decimal places, suppress scientific notation |
| 45 | + |
| 46 | +a = np.random.randint(0,10,5) |
| 47 | +a.sum() |
| 48 | +a.min() |
| 49 | +a.max() |
| 50 | +a.mean() |
| 51 | +a.var() # variance |
| 52 | +a.std() # standard deviation |
| 53 | + |
| 54 | + |
| 55 | +a.sum(axis=1) |
| 56 | +a.min(axis=0) |
| 57 | + |
| 58 | +a.argmin() # index of min element |
| 59 | +a.argmax() # index of max element |
| 60 | +a.argsort() # returns array of indices that would put the array in sorted order |
| 61 | +a.sort() # in place sort |
| 62 | + |
| 63 | +# indexing, slicing, iterating |
| 64 | +a = np.arange(10)**2 |
| 65 | +a[2] |
| 66 | +a[2:5] |
| 67 | + |
| 68 | +for i in a: |
| 69 | + print (i ** 2) |
| 70 | +a[::-1] # reverses array |
| 71 | + |
| 72 | +for i in a.flat: |
| 73 | + print (i) |
| 74 | + |
| 75 | + |
| 76 | +a.transpose() |
| 77 | + |
| 78 | +a.ravel() # flattens to 1D |
| 79 | + |
| 80 | +# read in csv data file |
| 81 | +data = np.loadtxt("data.txt", dtype=np.uint8, delimiter=",", skiprows=1 ) |
| 82 | +# loadtxt does not handle missing values. to handle such exceptions use genfromtxt instead. |
| 83 | + |
| 84 | +data = np.loadtxt("data.txt", dtype=np.uint8, delimiter=",", skiprows=1, usecols=[0,1,2,3]) |
| 85 | + |
| 86 | +np.random.shuffle(a) |
| 87 | + |
| 88 | +a = np.random.random(5) |
| 89 | + |
| 90 | +np.random.choice(a) |
| 91 | + |
| 92 | +np.random.random_integers(5,10,2) # (low, high inclusive, size) |
| 93 | + |
| 94 | + |
| 95 | + |
| 96 | + |
| 97 | + |
| 98 | + |
| 99 | + |
| 100 | + |
| 101 | + |
| 102 | + |
| 103 | + |
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| 105 | + |
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