How to Iterate Over Rows and Columns of Pandas DataFrame in Python

Iteration is the process of taking each item of overall items, one after another. Pandas DataFrame consists of rows and columns so, in order to iterate over DataFrame, we have to iterate a DataFramelike a dictionary. In a dictionary, we iterate over the keys of the object in the same way we have to iterate in DataFrame. In this article, I’ll show here how to iterate over Rows and Columns of Pandas DataFrame in Python.

In this article, I am using a sample DataFrame. Click here to see the topics. Here is the sample DataFrame:

       id      name  math_score
0  202301    Minhaj          92
1  202302   Ridhwan          86
2  202303   Tanveer          76
3  202304  Sharodia          89
4  202305      Alve          99
5  202306   Intisar          99

In Pandas DataFrame we can iterate an element in two ways:

  • Iterating over rows
  • Iterating over columns

Iterating Over Rows :

In order to iterate over rows, we can use three function iteritems(), iterrows(), itertuples() . These three function will help in iteration over rows.

Using iteritems() Method:

In order to iterate over rows, we apply a iterrows() function.  This function returns each index value along with a series containing the data in each row.

for i, j in df.iterrows():
    print(i, j)
    print()

Output:

0 id            202301
name          Minhaj
math_score        92
Name: 0, dtype: object

1 id             202302
name          Ridhwan
math_score         86
Name: 1, dtype: object

2 id             202303
name          Tanveer
math_score         76
Name: 2, dtype: object

3 id              202304
name          Sharodia
math_score          89
Name: 3, dtype: object

4 id            202305
name            Alve
math_score        99
Name: 4, dtype: object

5 id             202306
name          Intisar
math_score         99
Name: 5, dtype: object

Using iteritems() Method:

Now we apply a iteritems() function in order to retrieve an rows of dataframe.
for key, value in df.iteritems():
    print(key, value)
    print()
id 0    202301
1    202302
2    202303
3    202304
4    202305
5    202306
Name: id, dtype: object

name 0      Minhaj
1     Ridhwan
2     Tanveer
3    Sharodia
4        Alve
5     Intisar
Name: name, dtype: object

math_score 0    92
1    86
2    76
3    89
4    99
5    99
Name: math_score, dtype: int64
Using itertuples() Method
for i in df.itertuples():
    print(i)

Pandas(Index=0, id='202301', name='Minhaj', math_score=92)
Pandas(Index=1, id='202302', name='Ridhwan', math_score=86)
Pandas(Index=2, id='202303', name='Tanveer', math_score=76)
Pandas(Index=3, id='202304', name='Sharodia', math_score=89)
Pandas(Index=4, id='202305', name='Alve', math_score=99)
Pandas(Index=5, id='202306', name='Intisar', math_score=99)

Iterating Over Rows :

Now we iterate through columns in order to iterate through columns we first create a list of DataFrame columns and then iterate through list.
columns = list(df)
for i in columns:
# printing the third element of the column
print (df[i][2])

Output:

202303
Tanveer
76

In this tutorial, I tried to brief how to iterate over Rows and Columns of Pandas DataFrame in Python. Hope you have enjoyed the tutorial. If you want to get updated, like my facebook page https://www.facebook.com/LearningBigDataAnalytics and stay connected.

Add a Comment