Roman Roman - 6 months ago 50
Python Question

How to iterate over rows in a DataFrame?

I have a DataFrames 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 the above frame. For every row I want to be able to access its elements (values in cells) by the name of the columns. So, for example, I would like to have something like that:

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


Is it possible to do that in pandas?

I found 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.

Answer

iterrows is a generator which yield both index and row

In [18]: for index, row in df.iterrows():
   ....:     print row['c1'], row['c2']
   ....:     
10 100
11 110
12 120