Reference Excel in Python

Try pandas as well...might be easier to work with than lists in this case

DATA :

Width   Height
4           2
4           4
1           1
4           5

Code

import pandas as pd

#read the file
beam = pd.read_csv('cross_section.csv')         

beam['BeamSize'] = beam['Width']*beam['Height']  #do your calculations

Output:

>>> beam
   Width  Height  BeamSize
0      4       2         8
1      4       4        16
2      1       1         1
3      4       5        20
4      2       2         4

You can slice and dice the data as you wish. For eg, lets say you want the fifth beam :

>>> beam.ix[4]
Width       2
Height      2
BeamSize    4
Name: 4, dtype: int64

Check this for more info: http://pandas.pydata.org/pandas-docs/stable/

You can read directly from excel as well..

Thank you for you inputs. I have found the solution I was looking for by using Numpy.

data = np.loadtxt('C:\Users[User_Name]\Desktop[fname].csv', delimiter=',')

using that it took the data and created an array with the data that I needed. Now I am able to use the data like any other matrix or array.

If you don't mind adding a (somewhat heavy) dependency to your project, pandas has a read_excel function that can read a sheet from an Excel workbook into a pandas DataFrame object, which acts sort of like a dictionary. Then reading a cell would just amount to something like:

data = pd.read_excel('/path/to/file.xls')
cell_a1 = data.loc[1, 'a']  # or however it organizes it on import

For future readers of this question, it should be mentioned that xlrd is the "most exact" solution to your requirements. It will allow you to read data directly from an Excel file (no need to convert to CSV first).

Many other packages that read Excel files (including pandas) use xlrd themselves to provide that capability. They are useful, but "heavier" than xlrd (larger, more dependencies, may require compilation of C code, etc.).

(Incidentally, pandas happens to use both xlrd and NumPy.)