Call out data from 2D array to perform calculation

[poonck1]

I am now doing a linear regression analysis. The input variable is Size. The output variable is Price. I store the set of data in 2D array. I know using NumPy and SciPy is easy to conduct analysis but it only allows me to use for loop only to perform iterations. Therefore, I decided the following code to perform the calculation:

#Structure of array (Stored in float), with structure like this [Room, Price]
array = [[4.0, 399.9], [5.0, 329.9], [6.0, 369.0]]
#Set initial value
theta_price = 0
theta_room = 0
stepsize = 0.01
item = 3
#Perform iterations
for looping in range(0, 50): #Loop 50 times
         theta_price = theta_price - stepsize * (1 / item) * (sum([theta_price + theta_room * int(j) - int(k) for j, k in zip(array[0], array[1])]))#Perform iterations of theta 0
         theta_room = theta_room - stepsize * (1 / item) * (sum([(theta_price + theta_room * int(j) - int(k)) * int(j) for j, k in zip(array[0], array[1])]))#Perform iterations of theta 1
         theta_price = theta_price_1
         theta_room = theta_room_1
         print(theta_price,theta_room)#Print the result for every loop

However, the calculation is not what I am expected. I think it is because of the

zip(array[0], array[1])

which stores j as 4.0, 399.9 and k 5.0, 329.9 not j = 4.0, 5.0, 6.0 and k = 399.9, 329.9, 369.0.

To correct the error, I modified some of the code as

for looping in range(0, 50): #Loop 50 times
    for looping in range(0, (item-1)):
             theta_price = theta_price - stepsize * (1 / item) * (sum([theta_price + theta_room * int(j) - int(k) for j, k in zip(array[p][0], array[p][1])]))#Perform iterations of theta 0

Error:
zip argument #1 must support iteration

Therefore, how to correct the code to call out the data I want for calculation?

[buran]

you don't need zip at all

#Structure of array (Stored in float), with structure like this [Room, Price]
array = [[4.0, 399.9], [5.0, 329.9], [6.0, 369.0]]
#Set initial value
theta_price = 0
theta_room = 0
stepsize = 0.01
item = 3
#Perform iterations
for looping in range(0, 50): #Loop 50 times
   theta_price = theta_price - stepsize * (1 / item) * sum([theta_price + theta_room * int(j) - int(k) for j, k in array])#Perform iterations of theta 0
   theta_room = theta_room - stepsize * (1 / item) * sum([(theta_price + theta_room * int(j) - int(k)) * int(j) for j, k in array])#Perform iterations of theta 1
   print(theta_price,theta_room)#Print the result for every loop

---

you will need zip if you have 2 list and want to combine them:

>>> list1 = [1,2,3]
>>> list2 = [3,4,5]
>>> zip(list1,list2)
[(1, 3), (2, 4), (3, 5)]