python and pandas - how to access a column using iterrows

Question

wowee.....how to use iterrows with python and pandas? If I do a row iteration should I not be able to access a col with row['COL_NAME']?

Here are the col names:

print df Int64Index: 152 entries, 0 to 151 Data columns: Date          152  non-null values Time          152  non-null values Time Zone     152  non-null values Currency      152  non-null values Event         152  non-null values Importance    152  non-null values Actual        127  non-null values Forecast      86  non-null values Previous      132  non-null values dtypes: object(9)  for row in df.iterrows():     print row['Date']  Traceback (most recent call last):   File "/home/ubuntu/workspace/calandar.py", line 34, in <module>     print row['Date'] TypeError: tuple indices must be integers, not str 

if I print 1 row:

(0, Date                                                 Sun Apr 13 Time                                                      17:30 Time Zone                                                   GMT Currency                                                    USD Event         USD Fed's Stein Speaks on Financial Stability ... Importance                                                  Low Actual                                                      NaN Forecast                                                    NaN Previous                                                    NaN Name: 0) 

Answer 1

iterrows gives you (index, row) tuples rather than just the rows, so you should be able to access the columns in basically the same way you were thinking if you just do:

for index, row in df.iterrows():     print row['Date'] 

Answer 2

If you want to iterate across your database and apply a function to each row, you might also want to consider the apply function

def print_row(r):     print r['Date']  df.apply(print_row, axis = 1)