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NumPy Operations

Arithmetic

You can easily perform array with array arithmetic, or scalar with array arithmetic. Let's see some examples:



In [1]:

    
import numpy as np
arr = np.arange(0,10)



In [2]:

    
arr + arr









    Out[2]:





array([ 0,  2,  4,  6,  8, 10, 12, 14, 16, 18])



In [3]:

    
arr * arr









    Out[3]:





array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81])



In [4]:

    
arr - arr









    Out[4]:





array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])



In [5]:

    
# Warning on division by zero, but not an error!
# Just replaced with nan
arr/arr









    



C:\Users\AMurzabekov\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:3: RuntimeWarning: invalid value encountered in true_divide
  This is separate from the ipykernel package so we can avoid doing imports until






    Out[5]:





array([nan,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.])



In [6]:

    
# Also warning, but not an error instead infinity
1/arr









    



C:\Users\AMurzabekov\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:2: RuntimeWarning: divide by zero encountered in true_divide
  






    Out[6]:





array([       inf, 1.        , 0.5       , 0.33333333, 0.25      ,
       0.2       , 0.16666667, 0.14285714, 0.125     , 0.11111111])



In [7]:

    
arr**3









    Out[7]:





array([  0,   1,   8,  27,  64, 125, 216, 343, 512, 729], dtype=int32)

Universal Array Functions

Numpy comes with many universal array functions, which are essentially just mathematical operations you can use to perform the operation across the array. Let's show some common ones:



In [8]:

    
#Taking Square Roots
np.sqrt(arr)









    Out[8]:





array([0.        , 1.        , 1.41421356, 1.73205081, 2.        ,
       2.23606798, 2.44948974, 2.64575131, 2.82842712, 3.        ])



In [9]:

    
#Calcualting exponential (e^)
np.exp(arr)









    Out[9]:





array([1.00000000e+00, 2.71828183e+00, 7.38905610e+00, 2.00855369e+01,
       5.45981500e+01, 1.48413159e+02, 4.03428793e+02, 1.09663316e+03,
       2.98095799e+03, 8.10308393e+03])



In [10]:

    
np.max(arr) #same as arr.max()









    Out[10]:





9



In [11]:

    
np.sin(arr)









    Out[11]:





array([ 0.        ,  0.84147098,  0.90929743,  0.14112001, -0.7568025 ,
       -0.95892427, -0.2794155 ,  0.6569866 ,  0.98935825,  0.41211849])



In [12]:

    
np.log(arr)









    



C:\Users\AMurzabekov\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:1: RuntimeWarning: divide by zero encountered in log
  """Entry point for launching an IPython kernel.






    Out[12]:





array([      -inf, 0.        , 0.69314718, 1.09861229, 1.38629436,
       1.60943791, 1.79175947, 1.94591015, 2.07944154, 2.19722458])

Great Job!

That's all we need to know for now!