A **DataFrame** is a core data structure in **Pandas** used for storing and manipulating **Tabular Data**.

It provides many useful methods and features for analyzing, filtering, and transforming the data efficiently.

The general syntax of the `DataFrame` constructor is:

```js
import pandas as pd

pd.DataFrame(data, index=None, columns=None)
```

Here `index` and `column` are optional **named parameters**, which take up the default numerical values if not custom values are specified.

There are several ways to create a DataFrame:

## Dictionary of Lists
One of the most common methods is to use a dictionary where the **keys are column names** and the **values are lists of data**.



import pandas as pd

data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35],
    'City': ['New York', 'Paris', 'London']
}

df = pd.DataFrame(data)
print(df)

## List of Dictionaries
You can also pass a list of dictionaries, where each dictionary represents a row of data.

import pandas as pd

data = [
    {'Name': 'Alice', 'Age': 25, 'City': 'New York'},
    {'Name': 'Bob', 'Age': 30, 'City': 'Paris'},
    {'Name': 'Charlie', 'Age': 35, 'City': 'London'}
]

df = pd.DataFrame(data)
print(df)

## 2D List (List of Lists)
You can also use a list of lists (2D list). In this case you need to  explicitly specify the column names in the `DataFrame` constructor using the `columns` named parameter:

import pandas as pd

data = [
    ['Alice', 25, 'New York'],
    ['Bob', 30, 'Paris'],
    ['Charlie', 35, 'London']
]

df = pd.DataFrame(data, columns=['Name', 'Age', 'City'])
print(df)

Which of the following code snippets will create a DataFrame with columns `"Name"` and `"Age"`?

What does the `columns` argument in `pd.DataFrame()` do when using a **2D list**?

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.

Pandas: First Steps

What is a DataFrame?

Dictionary of Lists

List of Dictionaries

2D List (List of Lists)

1. What is a Pandas DataFrame?

2. Which of the following code snippets will create a DataFrame with columns `"Name"` and `"Age"`?

3. What does the `columns` argument in `pd.DataFrame()` do when using a 2D list?