Iterate over df

Pandas loop through rows

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

Output: 
   10 100
   11 110
   12 120

Source: stackoverflow.com

Iterate over rows dataframe

df = pd.DataFrame([{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}])
for index, row in df.iterrows():
    print(row['c1'], row['c2'])

Source: stackoverflow.com

Iterate over df

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

 #With iterrows method 

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

 #With itertuples method

 for row in df.itertuples(index=True, name='Pandas'):
     print(row.c1, row.c2)

Source: stackoverflow.com

Python - iterate with the data frame

# Option 1
for row in df.iterrows():
    print row.loc[0,'A']
    print row.A
    print row.index()

# Option 2
for i in range(len(df)) : 
  print(df.iloc[i, 0], df.iloc[i, 2])

Source: stackoverflow.com

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