#!/usr/bin/env python
# coding: utf-8

# In[7]:


import numpy as np

# Define a random list including 20 random integers between [1,56) 
random_list = np.random.randint(1,56,20)

#-----------------------------------------------
#Assign elements bigger than 28 in random_list to new_list 
new_list = [i for i in random_list if i>28 ]

print "Random Original List:", random_list
print "New list with the condition:", new_list

#------------------------------------------------
# Create a binary list including 1 or 0 according to the upper condition of elements in the random list.  
new_list_binary =  [1 if i>28 else 0 for i in random_list]

print "New binary list with the condition:", new_list_binary

#------------------------------------------------



    



# In[16]:


#Creating a list including list elements within a changing k range;
#------------------------------------------------
# List Comprehension Version

k= 9
new_list_comp = [[i for i in range(n)] for n in range (1,k+2)]
print "Creating a list with list comprehension, range: 9" ,new_list_comp
print ""
#------------------------------------------------
# Loop Version

new_list_loop = []
k=11
for n in range (1,k+2):
    temp_list = [] 
    for i in range(n):
         temp_list.append(i)
    new_list_loop.append(temp_list)     
          
print "Creating a list with loop, range: 11", new_list_loop

#------------------------------------------------


# In[17]:


# Using different new features of numpy
import numpy as np

# Creating a 5x6 (rowxcolumn) array including random integers between [1,26) 
new_matrix = np.random.randint(1,26,size=(5,6))
print new_matrix
print ""
print "Get the element at row 3 and column 4:", new_matrix[3,4]
print "Get the elements at row 1,2,3 and column 4:", new_matrix[1:4,4]
print "Get the elements at row 2 and column 3:4", new_matrix[2,3:5]
print ""
print "Max is  ", new_matrix.max()
print "Min is  ", new_matrix.min()
print "Mean is ", new_matrix.mean()
print ""
print "Find row based max:", new_matrix.max(axis=1)
print "Find column based max:", new_matrix.max(axis=0)


# In[29]:


#Drawing y=sin(x) and y= 3x^2+10

#When trying this example for canopy delete the line below
get_ipython().run_line_magic('matplotlib', 'inline')

import numpy as np
import matplotlib.pyplot as plt


x = np.linspace(0, 10, 30) #array of 30 points from 0 to 10
y_sin = np.sin(x)
y_curve=3*(x**2)+10                                    
ax1 = plt.subplot(211)                                    
plt.plot(x, y_curve, 'ro-', label='Curve : y=3x^2+10')
plt.legend(loc = 'lower right')
plt.xlabel("X axis")
plt.ylabel("Y axis") 

ax2= plt.subplot(212)                                    
plt.plot(x, y_sin, 'b-', label='A sine wave')
plt.legend(loc = 'lower right')
plt.xlabel("X axis")
plt.ylabel("Y axis") 

#When trying to show this example for canopy add the line below
#plt.show()



# In[37]:


#Drawing a histogram plot of ages distribution of a list containing 1000 people’s ages.

#When trying this example for canopy delete the line below
get_ipython().run_line_magic('matplotlib', 'inline')

import numpy as np
import matplotlib.pyplot as plt

#Loop ----------------------------------------

ages = []

for i in range(1000):
     ages.append(np.random.randint(10,61)) 

histogram = plt.hist(ages, bins=10)


#---------------------------------------------

#List Comprehension---------------------------

ages = [np.random.randint(10,61) for i in range(1000)]
histogram = plt.hist(ages, bins=10)

#----------------------------------------------

#Pure numpy features --------------------------

ages = np.random.randint(10,61,1000)
histogram = plt.hist(ages, bins=10)

#----------------------------------------------
#When trying to show this example for canopy add the line below
#plt.show()