Adding a constant column to a DataFrame is a common operation, and this article aims to provide a clear and concise guide on how to achieve this with Pandas.
Understanding Pandas DataFrame
A DataFrame is a two-dimensional, size-mutable, and potentially heterogeneous tabular data structure with labeled axes (rows and columns) in Pandas. It’s essential in organizing data in Python for analysis, resembling a spreadsheet or SQL table.
Why Add a Constant Column?
Adding a constant column to a DataFrame is useful in various scenarios such as tagging data with a specific attribute, initializing a column for further operations, or simply for data organization and structure.
Creating a Basic DataFrame
Start by creating a DataFrame. For our example, we’ll use a DataFrame with names.
import pandas as pd
names = ['Sachin', 'Manju', 'Ram', 'Raju', 'David', 'Freshers_In', 'Wilson']
df = pd.DataFrame(names, columns=['Name'])Adding a Constant Column
Now, let’s add a constant column to this DataFrame. We’ll add a column named ‘Category’ with a constant value ‘Participant’.
df['Category'] = 'Participant'
print(df)
This code will add a new column ‘Category’ to the DataFrame df, with all its values set to ‘Participant’..
