We can easily add new columns to an existing **DataFrame** using the **indexing** syntax:
```js
dataframe[column_name] = values
```

It is important that if `values` is a list, it needs to have the same number of elements as there are rows in the **DataFrame**, otherwise you'll get an error. Alternatively, we can assign a single value to the entire new column as well.

## Example 1: New Column from a Single Value

import pandas as pd

df = pd.DataFrame({
    'Product': ['Laptop', 'Tablet', 'Phone'],
    'Old Price': [1000, 600, 400]
})

# Add a new column with a fixed price for all rows
df['New Price'] = 700

print(df)

# Example 2: New Column using a List of Values

import pandas as pd

df = pd.DataFrame({
    'Member': ['Sophie', 'Liam', 'Emma'],
    'Role': ['Designer', 'Developer', 'Tester']
})

# Add a new column for Project Name
df['Project'] = ['Marketing Website Redesign', 'Client Portal Backend Development', 'Payment Flow QA Testing']

print(df)

## Example 3: New Column derived from Another Column

import pandas as pd

df = pd.DataFrame({
    'Product': ['Laptop', 'Tablet', 'Phone'],
    'Price': [1000, 600, 400]
})

# Derive a new column 'Discounted Price' (10% off)
df['Discounted Price'] = df['Price'] * 0.9

print(df)

What happens if you try to add a new column to a DataFrame with a list that has fewer elements than the number of rows?

Which of the following lines correctly adds a column `Discount` which is **20%** of the `Price`?

What would be the output of the following code?

In this course, we will explore the basics of Pandas – a powerful Python library for organizing, manipulating and analyzing data. Each concept will be explained through short and clear video lessons, followed by fun and practical microtasks, which are designed to help you understand the syntax and remember how to use different features and functions in Pandas with confidence.

In this section, we will explore some introductory concepts related to Pandas – which will help you get a basic understanding of the library and become more comfortable in working with it.

In this section, we will learn what are DataFrames, how to create them, and how to additional rows or columns to existing DataFrames. This section will prepare us for 
 the upcoming sections where we will explore more complex features of DataFrames.

In this section we will explore some methods of fetching data from DataFrames. Each topic will be accompanied with some tasks to help you with remembering the syntax and methods.

Adding new Columns

Example 1: New Column from a Single Value

Example 2: New Column using a List of Values

Example 3: New Column derived from Another Column

1. What happens if you try to add a new column to a DataFrame with a list that has fewer elements than the number of rows?

2. Which of the following lines correctly adds a column `Discount` which is 20% of the `Price`?

3. What would be the output of the following code?