Example 1: pandas loop through rows
for index, row in df.iterrows():
print(row['c1'], row['c2'])
Output:
10 100
11 110
12 120
Example 2: 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'])
Example 3: pandas iterate rows
import pandas as pd
import numpy as np
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
for index, row in df.iterrows():
print(row['c1'], row['c2'])
Example 4: python - iterate with the data frame
for row in df.iterrows():
print row.loc[0,'A']
print row.A
print row.index()
for i in range(len(df)) :
print(df.iloc[i, 0], df.iloc[i, 2])
Example 5: dataframe for loop
import pandas as pd
data = {'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka'],
'Age': [21, 19, 20, 18],
'Stream': ['Math', 'Commerce', 'Arts', 'Biology'],
'Percentage': [88, 92, 95, 70]}
df = pd.DataFrame(data, columns = ['Name', 'Age', 'Stream', 'Percentage'])
print("Given Dataframe :\n", df)
print("\nIterating over rows using iterrows() method :\n")
for index, row in df.iterrows():
print (row["Name"], row["Age"])
Example 6: how to iterate pandas dataframe
import pandas as pd
df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})
for index, row in df.iterrows():
print(row['c1'], row['c2'])