Pandas DataFrame iterrows() method is nothing but generates an iterator object of the DataFrame, allowing us to iterate each row in the pandas DataFrame. Each iteration produces an index object and a row object, a Pandas series object.
In Pandas, iteration is a general term for taking each item of something, one after another. It consists of rows and columns, so to iterate them over a data frame, we have to iterate a data frame like a dictionary in Pandas. The iterrows() method is 321 times faster than for loop. The primary function of iterrow() method is, it is used to iterate over a Pandas DataFrame rows in the form of index & series pair. It iterates over the data frame column and returns a tuple with the column name and content in the form of a series in Pandas.
This algorithm consists of instructions that are carried out one after another. It is mainly used in programming, which means repeating steps and instructions repeatedly, often called a loop. The advantages of iteration include working software from the start, and it delivers business value with each iteration. It is adaptable to changes in requirements throughout development.
Here is an example of Pandas iterrows in Python:
Fig : Preview of the output that you will get on running this code from your IDE.
Code
In this solution we're using Pandas library.
Instructions
Follow the steps carefully to get the output easily.
- Install pandas on your IDE(Any of your favorite IDE).
- Copy the snippet using the 'copy' and paste it in your IDE.
- Add required dependencies and import them in Python file.
- Run the file to generate the output.
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
I found this code snippet by searching for 'iterrows using pandas' in kandi. You can try any such use case!
Environment Tested
I tested this solution in the following versions. Be mindful of changes when working with other versions.
- The solution is created in PyCharm 2021.3.
- The solution is tested on Python 3.9.7.
- Pandas version-v1.5.2.
Using this solution, we are able to iterrows using pandas in python with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to iterrows using pandas in python.
Dependent Library
pandasby pandas-dev
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
pandasby pandas-dev
Python 38689 Version:v2.0.2 License: Permissive (BSD-3-Clause)
You can also search for any dependent libraries on kandi like 'pandas'.
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