Python Pandas is a powerful library to process data. Often you may need to iterate over rows in Pandas Dataframe. In this article, we will learn a couple of different ways to iterate over rows in Pandas DataFrame.
How to Iterate Over Rows in Pandas DataFrame
Let us say you have the following dataframe in python pandas.
import pandas as pd
inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
df = pd.DataFrame(inp)
print df
Here is the output you will see.
c1 c2 0 10 100 1 11 110 2 12 120
Let us say you want to iterate over the rows one by one and display their contents.
First, we will reset the index since we want to start from the first row.
df = df.reset_index() # make sure indexes pair with number of rows
Next, we will use dataframe.iterrows() to iterate through the rows of dataframe.
for index, row in df.iterrows():
print(row['c1'], row['c2'])
In the above loop, we directly print each row’s column values by using the column names. Here is the output you will see.
10 100 11 110 12 120
In this article, we have learnt how to iterate over rows in Pandas in Python.
Also read:
How to Get Row Count of Pandas DataFrame
How to Merge DataFrames in Pandas Based on Columns
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