How to iterate over rows in a DataFrame in Pandas?

I have a DataFrame from pandas:

    import pandas as pd
    inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
    df = pd.DataFrame(inp)
    print df

Output:

       c1   c2
    0  10  100
    1  11  110
    2  12  120

Now I want to iterate over the rows of this frame. For every row I want to be able to access its elements (values in cells) by the name of the columns. For example:

    for row in df.rows:
       print row['c1'], row['c2']

Is it possible to do that in pandas?

I found this similar question. But it does not give me the answer I need. For example, it is suggested there to use:

    for date, row in df.T.iteritems():

or

    for row in df.iterrows():

But I do not understand what the row object is and how I can work with it.

iterrows is a generator which yield both index and row

    for index, row in df.iterrows():
       print row['c1'], row['c2']

    Output: 
       10 100
       11 110
       12 120

From: stackoverflow.com/q/16476924

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