name_map = {'oldcol1': 'newcol1', 'oldcol2': 'newcol2', 'oldcol3': 'newcol3'...}

for row in rows:
    # Each row is a dict of the form: {'oldcol1': '...', 'oldcol2': '...'}
    row = dict((name_map[name], val) for name, val in row.iteritems())
    ...

Or in Python2.7+ with Dict Comprehensions:

for row in rows:
    row = {name_map[name]: val for name, val in row.items()}

There is no such function; the easiest way to do this is to use a dict comprehension:

my_dictionary = {k: f(v) for k, v in my_dictionary.items()}

Note that there is no such method on lists either; you'd have to use a list comprehension or the map() function.

As such, you could use the map() function for processing your dict as well:

my_dictionary = dict(map(lambda kv: (kv[0], f(kv[1])), my_dictionary.items()))

but that's not that readable, really.

(Note that if you're still using Python 2.7, you should use the .iteritems() method instead of .items() to save memory. Also, the dict comprehension syntax wasn't introduced until Python 2.7.)

In Python 3, map returns an iterator, not a list. You still have to iterate over it, either by calling list on it explicitly, or by putting it in a for loop. But you shouldn't use map this way anyway. map is really for collecting return values into an iterable or sequence. Since neither print nor set.update returns a value, using map in this case isn't idiomatic.

Your goal is to put all the keys in all the counters in counters into a single set. One way to do that is to use a nested generator expression:

s = set(key for counter in counters.values() for key in counter)

There's also the lovely dict comprehension syntax, which is available in Python 2.7 and higher (thanks Lattyware!) and can generate sets as well as dictionaries:

s = {key for counter in counters.values() for key in counter}

These are both roughly equivalent to the following:

s = set()
for counter in counters.values():
    for key in counter:
        s.add(key)