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: pandas iterrows
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 3: 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 4: iterrows pandas
>>> df = pd.DataFrame([[1, 1.5]], columns=['int', 'float'])
>>> row = next(df.iterrows())[1]
>>> row
int 1.0
float 1.5
Name: 0, dtype: float64
>>> print(row['int'].dtype)
float64
>>> print(df['int'].dtype)
int64