26 Oct Iterate over rows and columns in a Pandas DataFrame

In this lesson, we will learn how to iterate over rows and columns in a Pandas DataFrame. Let’s see examples of how to:

1. Iterate over rows
2. Iterate over columns

Before moving further, we’ve prepared a video tutorial to iterate over rows and columns in a Pandas DataFrame:

Iterate over rows

To iterate over the rows, use the following methods in Pandas:

• iterrows(): To Iterate over the rows
• itertuples(): To Iterate over the rows

Pandas iterrows() to iterate over rows

To iterate over rows, use the Python Pandas iterrows() method. Here, we are only displaying the student names from the student records. Let us see an example:

import pandas as pd
 
# Dataset
data = {
  'id': ["S01", "S02", "S03", "S04", "S05"],
  'student': ["Amit", "John", "Jacob", "David", "Steve"],
  'rank': [1, 4, 3, 5, 2]
}
 
dataFrame = pd.DataFrame(data)
print("Student Records\n", dataFrame)

# Iterate over rows in the DataFrames
print("\nDisplay the rows")
for row in dataFrame.iterrows():
  print(row)

Output

Student Records
     id student  rank
0  S01    Amit     1
1  S02    John     4
2  S03   Jacob     3
3  S04   David     5
4  S05   Steve     2

Display the rows
(0, id          S01
student    Amit
rank          1
Name: 0, dtype: object)
(1, id          S02
student    John
rank          4
Name: 1, dtype: object)
(2, id           S03
student    Jacob
rank           3
Name: 2, dtype: object)
(3, id           S04
student    David
rank           5
Name: 3, dtype: object)
(4, id           S05
student    Steve
rank           2
Name: 4, dtype: object)

Pandas itertuples() to iterate over rows

To iterate over rows, use the Python Pandas itertuples() method. Here, each row is returned as a Python Tuple object. Here, we are only displaying the student names from the student records

Let us see an example:

import pandas as pd
 
# Dataset
data = {
  'id': ["S01", "S02", "S03", "S04", "S05"],
  'student': ["Amit", "John", "Jacob", "David", "Steve"],
  'rank': [1, 4, 3, 5, 2]
}
 
dataFrame = pd.DataFrame(data)
print("Student Records\n", dataFrame)

# Iterate over rows in the DataFrames
print("\nDisplay records as a Tuple object")
for row in dataFrame.itertuples():
  print(row)

Output

Student Records
     id student  rank
0  S01    Amit     1
1  S02    John     4
2  S03   Jacob     3
3  S04   David     5
4  S05   Steve     2

Display records as a Python object
Pandas(Index=0, id='S01', student='Amit', rank=1)
Pandas(Index=1, id='S02', student='John', rank=4)
Pandas(Index=2, id='S03', student='Jacob', rank=3)
Pandas(Index=3, id='S04', student='David', rank=5)
Pandas(Index=4, id='S05', student='Steve', rank=2)

Iterate over columns

To iterate over columns, use the following methods in Pandas:

• items(): To Iterate over the columns
• iteritems(): To Iterate over the columns (Deprecated now)

Pandas items() to iterate over columns

To iterate each and every column, use the Pandas items() method. The result will display a label object that is the name of the column and a column object that is what you have in the column.

Let us see an example to iterate over columns:

import pandas as pd
 
# Dataset
data = {
  'id': ["S01", "S02", "S03", "S04", "S05"],
  'student': ["Amit", "John", "Jacob", "David", "Steve"],
  'rank': [1, 4, 3, 5, 2]
}
 
dataFrame = pd.DataFrame(data)
print("Student Records\n")

# Iterate over columns in the DataFrame
for a, b in dataFrame.items():
  print(a)
  print(b)

Output

Student Records

id
0    S01
1    S02
2    S03
3    S04
4    S05
Name: id, dtype: object
student
0     Amit
1     John
2    Jacob
3    David
4    Steve
Name: student, dtype: object
rank
0    1
1    4
2    3
3    5
4    2
Name: rank, dtype: int64

Pandas iteritems() to iterate over columns

The Pandas itertems() method was deprecated. Use the items() as shown above to iterate over columns.

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