How to select DataFrame columns based on partial matching?

Select column by partial string, can simply be done, via:

df.filter(like='hello')  # select columns which contain the word hello

And to select rows by partial string match, you can pass axis=0 to filter:

df.filter(like='hello', axis=0) 

I think df.keys().tolist() is the thing you're searching for.

A tiny example:

from pandas import DataFrame as df

d = df({'somename': [1,2,3], 'othername': [4,5,6]})

names = d.keys().tolist()

for n in names:
    print n
    print type(n)

Output:

othername
type 'str'

somename
type 'str'

Then with the strings you got, you can do any string operation you want.

Your solution using map is very good. If you really want to use str.contains, it is possible to convert Index objects to Series (which have the str.contains method):

In [1]: df
Out[1]: 
   x  y  z
0  0  0  0
1  1  1  1
2  2  2  2
3  3  3  3
4  4  4  4
5  5  5  5
6  6  6  6
7  7  7  7
8  8  8  8
9  9  9  9

In [2]: df.columns.to_series().str.contains('x')
Out[2]: 
x     True
y    False
z    False
dtype: bool

In [3]: df[df.columns[df.columns.to_series().str.contains('x')]]
Out[3]: 
   x
0  0
1  1
2  2
3  3
4  4
5  5
6  6
7  7
8  8
9  9

UPDATE I just read your last paragraph. From the documentation, str.contains allows you to pass a regex by default (str.contains('^myregex'))