In [1]:

    

import sympy
x = sympy.symbols('x')
f = sympy.symbols('f', cls=sympy.Function)
f = sympy.exp(x)
f.series?


    

In [2]:

    

%matplotlib inline
import numpy
import matplotlib.pyplot as plt


    

In [3]:

    

x = numpy.linspace(0,10,100)
print(x)


    

    




[  0.           0.1010101    0.2020202    0.3030303    0.4040404
   0.50505051   0.60606061   0.70707071   0.80808081   0.90909091
   1.01010101   1.11111111   1.21212121   1.31313131   1.41414141
   1.51515152   1.61616162   1.71717172   1.81818182   1.91919192
   2.02020202   2.12121212   2.22222222   2.32323232   2.42424242
   2.52525253   2.62626263   2.72727273   2.82828283   2.92929293
   3.03030303   3.13131313   3.23232323   3.33333333   3.43434343
   3.53535354   3.63636364   3.73737374   3.83838384   3.93939394
   4.04040404   4.14141414   4.24242424   4.34343434   4.44444444
   4.54545455   4.64646465   4.74747475   4.84848485   4.94949495
   5.05050505   5.15151515   5.25252525   5.35353535   5.45454545
   5.55555556   5.65656566   5.75757576   5.85858586   5.95959596
   6.06060606   6.16161616   6.26262626   6.36363636   6.46464646
   6.56565657   6.66666667   6.76767677   6.86868687   6.96969697
   7.07070707   7.17171717   7.27272727   7.37373737   7.47474747
   7.57575758   7.67676768   7.77777778   7.87878788   7.97979798
   8.08080808   8.18181818   8.28282828   8.38383838   8.48484848
   8.58585859   8.68686869   8.78787879   8.88888889   8.98989899
   9.09090909   9.19191919   9.29292929   9.39393939   9.49494949
   9.5959596    9.6969697    9.7979798    9.8989899   10.        ]

In [5]:

    

y = numpy.random?


    

In [6]:

    

y = numpy.random.random_sample?


    

In [10]:

    

y = [0]
for i in range(99):
    y = y + [numpy.random.random_sample()]
print(len(y))


    

    




100

In [11]:

    

plt.plot(x,y)


    

    
Out[11]:





[<matplotlib.lines.Line2D at 0x81e3cc0>]






    

In [ ]: