Importing Pandas conventions - Mini Project: Build & Apply

Importing Pandas Conventions

📖 Scenario: You are starting a data science project where you need to work with tables of data. To do this, you will use the pandas library, which helps you handle data easily.

🎯 Goal: Learn how to import the pandas library using the common short name pd. This will help you write shorter and clearer code when working with data tables.

📋 What You'll Learn

Import the pandas library using the alias pd

💡 Why This Matters

🌍 Real World

Pandas is used in many jobs to handle data from sales, customers, or experiments. Importing pandas correctly is the first step to working with data tables.

💼 Career

Data analysts and data scientists use pandas daily to clean, analyze, and visualize data. Knowing how to import pandas with the common alias <code>pd</code> is a basic but important skill.

1

Import the pandas library

Write the code to import the pandas library using the alias pd. This means you will write import pandas as pd exactly.

Pandas

# Your code here

Need a hint?

Use the syntax import pandas as pd to import pandas with the short name pd.

2

Create a simple pandas DataFrame

Create a pandas DataFrame called data using pd.DataFrame with this dictionary: {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}.

Pandas

import pandas as pd
# Your code here

Need a hint?

Use pd.DataFrame and pass the dictionary with keys 'Name' and 'Age' and their lists of values.

3

Check the type of the DataFrame

Write a line to create a variable called data_type that stores the type of data using the type() function.

Pandas

import pandas as pd

data = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
# Your code here

Need a hint?

Use data_type = type(data) to get the type of the DataFrame.

4

Print the type of the DataFrame

Write a print statement to display the value of data_type.

Pandas

import pandas as pd

data = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
data_type = type(data)
# Your code here

Need a hint?

Use print(data_type) to show the type of the DataFrame.