In this post, we are going to construct a unit conversion table in python. The table will have columns for meters (m), centimeter (cm), and inches (in). We will start off with a list of values that will be our meter collumn.



In [1]:

    
meters = [0, 10, 20, 30, 40, 50]



In [2]:

    
meters









    Out[2]:





[0, 10, 20, 30, 40, 50]



In [5]:

    
centimeters = meters*0.01
centimeters









    



---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-5-5c4be8cc688b> in <module>()
----> 1 centimeters = meters*0.01
      2 centimeters

TypeError: can't multiply sequence by non-int of type 'float'

One way we can accomplish this is with list comprehensions.



In [7]:

    
centimeters = [value*100 for value in meters]
centimeters









    Out[7]:





[0, 1000, 2000, 3000, 4000, 5000]

We can also create our originol meter list in a more dynamic way.



In [3]:

    
meters = list(range(11))
meters = [value*10 for value in meters]
meters









    Out[3]:





[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100]

Another way to accomplish this same thing is to use numpy's array function



In [4]:

    
import numpy as np



In [10]:

    
meters = np.arange(0,110,10)
meters









    Out[10]:





array([  0,  10,  20,  30,  40,  50,  60,  70,  80,  90, 100])

Now making the centimeters list is a little easier, because we can multiply each value in the array by the scalar 100 with one opperation and no need for list comprehensions.



In [11]:

    
centimeters = meters*100
centimeters









    Out[11]:





array([    0,  1000,  2000,  3000,  4000,  5000,  6000,  7000,  8000,
        9000, 10000])



In [20]:

    
table = np.concatenate((meters,centimeters),axis=0)
print(table)









    



[    0    10    20    30    40    50    60    70    80    90   100     0
  1000  2000  3000  4000  5000  6000  7000  8000  9000 10000]



In [28]:

    
np.reshape(table,(2,11))
table









    Out[28]:





array([    0,    10,    20,    30,    40,    50,    60,    70,    80,
          90,   100,     0,  1000,  2000,  3000,  4000,  5000,  6000,
        7000,  8000,  9000, 10000])



In [29]:

    
table.shape









    Out[29]:





(22,)



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