Python sample code for bind rows into a data frame | S-Logix

List of Topics:

How to Bind Rows into DataFrame in Python

Bind Rows into DataFrame in Python

Condition for Binding Rows into DataFrame in Python

Description:
Binding rows into a DataFrame means combining multiple rows or entire DataFrames into one unified DataFrame. This is often used when data from different sources or subsets needs to be consolidated.

Step-by-Step Process

Import Pandas:
Import the library to work with DataFrames.
Prepare Data:
Create the rows or DataFrames to be combined. Ensure they have the same column structure.
Bind Rows:
Use pd.concat() to combine them.
Verify the Result:
Check the resulting DataFrame to ensure proper alignment.

Sample Source Code

# Binding rows using 2 dataframe

import pandas as pd

df1 = pd.DataFrame({
'Name': ['Praveen', 'Kanth', 'kumar'],
'Age': [25, 22, 20],
'Role': ['Python', 'Java', 'C']
})

# 2nd dataframe for binding
df2 = pd.DataFrame({
'Name': ['Surya', 'David'],
'Age': [35, 40],
'Role': ['C++', 'Python']
})

# Binding rows using concatenation
result = pd.concat([df1, df2], ignore_index=True)

print(result)

Screenshots

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