Need some basic Pandas help -- trying to print a dataframe row by row and perform operations on the elements within specific columns of that row

Question

Basically, I have a query returning a dataframe and row by row I want to generate new queries using the elements of the row as arguments for the next query -- the example walks through a simplified version and understanding that should be sufficient!

>>> import pandas as pd
>>> df2 = pd.DataFrame({'a' : ['colorado', 'california', 'texas', 'oregon'], 'b' : ['go buffs', 'go bears', 'go sooners', 'go ducks'], 'c' : [14,14,15,13]})
>>> df2
            a           b   c
0    colorado    go buffs  14
1  california    go bears  14
2       texas  go sooners  15
3      oregon    go ducks  13

#Print element by element in column
>>> for x in df2['a']:
...     print x
...
colorado
california
texas
oregon

#What I want is to print full ROWS

>>> df3 = df2.loc[:, ['a','b']]
>>> df3
            a           b
0    colorado    go buffs
1  california    go bears
2       texas  go sooners
3      oregon    go ducks

#I want to get something like
#for x, y in df3['a','b']:
#       print 'in %s say %s!'%(x,y)

#and get:
#in colorado say go buffs!
#in california....etc

#How do I do that!?

Answer 1

You can unroll the tuples as you iterate through the dataframe and then just print the columns you desire:

for row in df2.itertuples():
    index, a, b, c  = row
    print 'in %s say %s!'%(a,b)

in colorado say go buffs!
in california say go bears!
in texas say go sooners!
in oregon say go ducks!

Alternatively you can use iterrows which as @DSM pointed out returns an index with nested values (actually a Series):

for row in df2.iterrows():
    index, data = row
    print 'in %s say %s!' % (data['a'], data['b'])

This will also output the same as the first code snippet