iterate through dataframe python

# import pandas package as pd 
import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using iterrows() method :\n") 
  
# iterate through each row and select  
# 'Name' and 'Age' column respectively. 
for index, row in df.iterrows(): 
    print (row["Name"], row["Age"]) 

# import pandas package as pd 
import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using loc function :\n") 
  
# iterate through each row and select  
# 'Name' and 'Age' column respectively. 
for i in range(len(df)) : 
  print(df.loc[i, "Name"], df.loc[i, "Age"]) 

# import pandas package as pd 
import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using apply function :\n") 
  
# iterate through each row and concatenate 
# 'Name' and 'Percentage' column respectively. 
print(df.apply(lambda row: row["Name"] + " " + str(row["Percentage"]), axis = 1)) 


# iterating through rows checking current index and compare to next index
# for duplicates


or index, row in dfmwf.iterrows():
        current = dfmwf.loc[index, 'ID']
        if current == dfmwf.shift(+1).loc[index, 'ID']:
                print('yes, it is a dupicate')
                count += 1
        else:
                print('nope')
                count += 1    

df.shift(-1).iloc[index,5]

# import pandas package as pd 
import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using iloc function :\n") 
  
# iterate through each row and select  
# 0th and 2nd index column respectively. 
for i in range(len(df)) : 
  print(df.iloc[i, 0], df.iloc[i, 2]) 

# import pandas package as pd 
import pandas as pd 
  
# Define a dictionary containing students data 
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'], 
                'Age': [21, 19, 20, 18], 
                'Stream': ['Math', 'Commerce', 'Arts', 'Biology'], 
                'Percentage': [88, 92, 95, 70]} 
  
# Convert the dictionary into DataFrame 
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage']) 
  
print("Given Dataframe :\n", df) 
  
print("\nIterating over rows using itertuples() method :\n") 
  
# iterate through each row and select  
# 'Name' and 'Percentage' column respectively. 
for row in df.itertuples(index = True, name ='Pandas'): 
    print (getattr(row, "Name"), getattr(row, "Percentage"))