How can I create a DataFrame from multiple numpy arrays, Pandas Series, or Pandas DataFrame's while preserving the order of the columns?

For example, I have these two numpy arrays and I want to combine them as a Pandas DataFrame.

foo = np.array( [ 1, 2, 3 ] )
bar = np.array( [ 4, 5, 6 ] )

If I do this, the bar column would come first because dict doesn't preserve order.

pd.DataFrame( { 'foo': pd.Series(foo), 'bar': pd.Series(bar) } )bar foo
0   4   1
1   5   2
2   6   3

I can do this, but it gets tedious when I need to combine many variables.

pd.DataFrame( { 'foo': pd.Series(foo), 'bar': pd.Series(bar) }, columns = [ 'foo', 'bar' ] )

EDIT: Is there a way to specify the variables to be joined and to organize the column order in one operation? That is, I don't mind using multiple lines to complete the entire operation, but I'd rather not having to specify the variables to be joined multiple times (since I will be changing the code a lot and this is pretty error prone).

EDIT2: One more point. If I want to add or remove one of the variables to be joined, I only want to add/remove in one place.

Original Solution: Incorrect Usage of collections.OrderedDict

In my original solution, I proposed to use OrderedDict from the collections package in python's standard library.

>>> import numpy as np
>>> import pandas as pd
>>> from collections import OrderedDict
>>>
>>> foo = np.array( [ 1, 2, 3 ] )
>>> bar = np.array( [ 4, 5, 6 ] )
>>>
>>> pd.DataFrame( OrderedDict( { 'foo': pd.Series(foo), 'bar': pd.Series(bar) } ) )foo  bar
0    1    4
1    2    5
2    3    6

Right Solution: Passing Key-Value Tuple Pairs for Order Preservation

However, as noted, if a normal dictionary is passed to OrderedDict, the order may still not be preserved since the order is randomized when constructing the dictionary. However, a work around is to convert a list of key-value tuple pairs into an OrderedDict, as suggested from this SO post:

>>> import numpy as np
>>> import pandas as pd
>>> from collections import OrderedDict
>>>
>>> a = np.array( [ 1, 2, 3 ] )
>>> b = np.array( [ 4, 5, 6 ] )
>>> c = np.array( [ 7, 8, 9 ] )
>>>
>>> pd.DataFrame( OrderedDict( { 'a': pd.Series(a), 'b': pd.Series(b), 'c': pd.Series(c) } ) )a  c  b
0  1  7  4
1  2  8  5
2  3  9  6>>> pd.DataFrame( OrderedDict( (('a', pd.Series(a)), ('b', pd.Series(b)), ('c', pd.Series(c))) ) )a  b  c
0  1  4  7
1  2  5  8
2  3  6  9