Pandas DataFrame iterrows() Method

In this tutorial, we will learn the Python pandas DataFrame.iterrows() method. This method iterates over rows as (index, Series) pairs. When this method applied to the DataFrame, it iterates over the DataFrame rows and returns a tuple which consists of column name and the content as a Series.

The below shows the syntax of the DataFrame.iterrows() method.

Syntax

DataFrame.iterrows()

Example: Iterate over the rows name using the DataFrame.iterrows() Method

When we use the DataFrame.iterrows() method to iterate over the rows of the DataFrame, it will return the generator object. See the below example.

#importing pandas as pd
import pandas as pd
#creating DataFrame
df=pd.DataFrame({"Name":["Navya","Vindya"],"Age":[25,24],"Education":["M.Tech","Ph.d"]},index=['id001', 'id002'])
print("-----------The DataFrame is-------")
print(df)
print("---------Iterate over rows name---------")
print(df.iterrows())

-----------The DataFrame is-------
Name Age Education
id001 Navya 25 M.Tech
id002 Vindya 24 Ph.d
---------Iterate over rows name---------
<generator object DataFrame.iterrows at 0x000001E34195B890>

Example: The DataFrame.iterrows() Method

In the last example, we understand that when we use the DataFrame.iterrows() method to iterate over the rows of the DataFrame, it will return the generator object. By using the for loop, we can use this object to generate a pair of index_name and the data. See the below example.

#importing pandas as pd
import pandas as pd
#creating DataFrame
df=pd.DataFrame({"Name":["Navya","Vindya"],"Age":[25,24],"Education":["M.Tech","Ph.d"]},index=['id001', 'id002'])
print("---------Iterate over rows name---------")
for column_name,data in df.iterrows():
    print('index_name:',column_name,'data:',data)

Once we run the program we will get the following output.

---------Iterate over rows name---------
index_name: id001 data: Name Navya
Age 25
Education M.Tech
Name: id001, dtype: object
index_name: id002 data: Name Vindya
Age 24
Education Ph.d
Name: id002, dtype: object

Example: The DataFrame.iterrows() Method

We can also print a certain row by specifying the index number. See the below example.

#importing pandas as pd
import pandas as pd
#creating DataFrame
df=pd.DataFrame({"Name":["Navya","Vindya"],"Age":[25,24],"Education":["M.Tech","Ph.d"]},index=['id001', 'id002'])
print("---------Iterate over rows name---------")
for column_name,data in df.iterrows():
    print('index_name:',column_name,'data:',data[0])

---------Iterate over rows name---------
index_name: id001 data: Navya
index_name: id002 data: Vindya

Example: The DataFrame.iterrows() Method

We can also specify the name of the column instead of the column name. See the below example.

#importing pandas as pd
import pandas as pd
#creating DataFrame
df=pd.DataFrame({"Name":["Navya","Vindya"],"Age":[25,24],"Education":["M.Tech","Ph.d"]},index=['id001', 'id002'])
print("-----------The DataFrame is-------")
print(df)
print("---------Iterate over rows name---------")
for column_name,data in df.iterrows():
    print('index_name:',column_name,'data:',data['Name'])

-----------The DataFrame is-------
Name Age Education
id001 Navya 25 M.Tech
id002 Vindya 24 Ph.d
---------Iterate over rows name---------
index_name: id001 data: Navya
index_name: id002 data: Vindya

Conclusion:

In this tutorial, we learned the Python pandas DataFrame.iterrows() method. We learned the syntax and by applying this method on the DataFrame.