[FIXED] How to iterate over rows in a DataFrame in Pandas

Issue

I have a pandas dataframe, df:

   c1   c2
0  10  100
1  11  110
2  12  120

How do I iterate over the rows of this dataframe? 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'])

---

I found a similar question which suggests using either of these:

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

for row in df.iterrows():

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

Solution

DataFrame.iterrows is a generator which yields both the index and row (as a Series):

import pandas as pd

df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
df = df.reset_index()  # make sure indexes pair with number of rows

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

10 100
11 110
12 120

Answered By - waitingkuo