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In [2]:

    
1+1









    Out[2]:





2



In [3]:

    
def print_hello():
    print('hello')
    
print_hello()









    



hello



In [4]:

    
import numpy as np



In [5]:

    
class Hello():
    def __init__(self, to_say):
        self.to_say = to_say
        
    def say_it(self):
        print(f'hello {self.to_say}')



In [6]:

    
h = Hello('Hakan')



In [7]:

    
h.say_it()









    



hello Hakan



In [8]:

    
print_hello()









    



hello

Workshop

Thing 1
Thing 2 Link: http://fast.ai



In [11]:

    
a = [1,2]; a









    Out[11]:





[1, 2]



In [12]:

    
for i in range(5): print(i+1)



In [25]:

    
# a = [... for i in ...]; a
a = [i+1 for i in range(5)]; a









    Out[25]:





[1, 2, 3, 4, 5]



In [23]:

    
[i*2 for i in a]









    Out[23]:





[2, 6, 10, 14, 18]



In [24]:

    
def modify_a(it): return it * 2 + 1



In [26]:

    
a = [modify_a(i) for i in range(5)]; a









    Out[26]:





[1, 3, 5, 7, 9]

A reduction in Informatics takes a list and returns a reduction. Example: the sum() operation



In [27]:

    
sum(a)









    Out[27]:





25



In [35]:

    
def modify_a(it): return [str(it*2+1)]

Map / Reduce:



In [36]:

    
a = [modify_a(i) for i in range(5)]; a









    Out[36]:





[['1'], ['3'], ['5'], ['7'], ['9']]



In [37]:

    
sum(a, [])









    Out[37]:





['1', '3', '5', '7', '9']

Filter



In [38]:

    
a = [modify_a(i) for i in range(5) if i%2==0]; a









    Out[38]:





[['1'], ['5'], ['9']]



In [41]:

    
sum(a, [])









    Out[41]:





['1', '5', '9']



In [43]:

    
{'a':1, 'b':2}









    Out[43]:





{'a': 1, 'b': 2}



In [46]:

    
v = ['the', 'a', 'you']; v









    Out[46]:





['the', 'a', 'you']



In [48]:

    
[(i,w) for i,w in enumerate(v)]









    Out[48]:





[(0, 'the'), (1, 'a'), (2, 'you')]



In [49]:

    
{w:i for i,w in enumerate(v)}









    Out[49]:





{'a': 1, 'the': 0, 'you': 2}



In [50]:

    
import numpy as np



In [51]:

    
a = np.array([1,2,3]); a









    Out[51]:





array([1, 2, 3])



In [52]:

    
a*2









    Out[52]:





array([2, 4, 6])



In [53]:

    
a = np.array([1.1, 2.3, -3]);a









    Out[53]:





array([ 1.1,  2.3, -3. ])



In [54]:

    
a*2









    Out[54]:





array([ 2.2,  4.6, -6. ])



In [55]:

    
a.round(1)









    Out[55]:





array([ 1.1,  2.3, -3. ])



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