What is Pandas - Hands-On Activity

What is Pandas

📖 Scenario: You are starting to learn data science. You want to understand what Pandas is and how to create a simple data table using it.

🎯 Goal: Learn what Pandas is and create a simple table (DataFrame) with it.

📋 What You'll Learn

Create a Pandas DataFrame from a dictionary

Understand that Pandas helps organize data in tables

Print the DataFrame to see the data

💡 Why This Matters

🌍 Real World

Pandas is used to organize data from surveys, sales, or any list of information to make it easy to analyze.

💼 Career

Data scientists and analysts use Pandas daily to clean, explore, and prepare data for reports and machine learning.

1

Create a dictionary with sample data

Create a dictionary called data with these exact entries: 'Name': ['Alice', 'Bob', 'Charlie'] and 'Age': [25, 30, 35].

Pandas

# Create the dictionary called data
# Your code here

Hint

Use curly braces {} to create a dictionary. The keys are 'Name' and 'Age'. The values are lists of names and ages.

2

Import Pandas library

Write the exact line import pandas as pd to import the Pandas library with the alias pd.

Pandas

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
# Import pandas as pd
# Your code here

Hint

Use the import keyword followed by pandas as pd.

3

Create a DataFrame from the dictionary

Create a Pandas DataFrame called df from the dictionary data using pd.DataFrame(data).

Pandas

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
import pandas as pd
# Create DataFrame df from data
# Your code here

Hint

Use pd.DataFrame() and pass the data dictionary inside the parentheses.

4

Print the DataFrame

Write print(df) to display the DataFrame df.

Pandas

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
import pandas as pd
df = pd.DataFrame(data)
# Print the DataFrame df
# Your code here

Hint

Use the print() function with df inside to show the table.

Practice

1. What is pandas mainly used for in Python?

easy

A. Writing system drivers

B. Creating 3D graphics

C. Building websites

D. Working with tables of data easily

Solution

1. Step 1: Understand pandas purpose

   Pandas is a Python library designed to handle and analyze data in tables.

2. Step 2: Match purpose with options

   Only Working with tables of data easily describes working with tables of data, which matches pandas' main use.

3. Final Answer:

   Working with tables of data easily -> Option D

4. Quick Check:

   pandas = tables of data [OK]

Hint: Remember pandas = data tables in Python [OK]

Common Mistakes:

• Confusing pandas with graphics or web tools
• Thinking pandas is for system programming

2. Which of these is the correct way to import pandas in Python?

easy

A. import pandas as pn

B. import pandas as pd

C. from pandas import table

D. import panda as pd

Solution

1. Step 1: Recall pandas import convention

   The common and correct way is to import pandas as pd for short.

2. Step 2: Check each option

   import pandas as pd matches the standard import. Others have wrong names or syntax.

3. Final Answer:

   import pandas as pd -> Option B

4. Quick Check:

   Standard import = import pandas as pd [OK]

Hint: Use 'import pandas as pd' always [OK]

Common Mistakes:

• Misspelling 'pandas' as 'panda'
• Using wrong alias like 'pn'
• Trying to import non-existent modules

3. What will this code print?

import pandas as pd
data = {'A': [1, 2], 'B': [3, 4]}
df = pd.DataFrame(data)
print(df)

medium

A. A table with columns A and B showing values 1,2 and 3,4

B. A list of dictionaries

C. An error because DataFrame is not defined

D. Empty output

Solution

1. Step 1: Create DataFrame from dictionary

   The dictionary has keys 'A' and 'B' with lists as values. pd.DataFrame converts this into a table with columns A and B.

2. Step 2: Print DataFrame

   Printing df shows a table with two rows: first row 1 and 3, second row 2 and 4 under columns A and B.

3. Final Answer:

   A table with columns A and B showing values 1,2 and 3,4 -> Option A

4. Quick Check:

   DataFrame prints table = A table with columns A and B showing values 1,2 and 3,4 [OK]

Hint: DataFrame from dict shows columns and rows [OK]

Common Mistakes:

• Thinking it prints a list or dictionary
• Expecting an error without importing pandas
• Assuming empty output

4. Find the error in this code:

import pandas as pd
data = {'X': [5, 6], 'Y': [7, 8]}
df = pd.Dataframe(data)
print(df)

medium

A. Typo in DataFrame capitalization

B. Missing import statement

C. Dictionary keys must be strings

D. print() function is incorrect

Solution

1. Step 1: Check pandas DataFrame spelling

   The correct class name is DataFrame with a capital 'F'. The code uses Dataframe which causes an error.

2. Step 2: Verify other parts

   Import is correct, dictionary keys are strings, and print() is used properly.

3. Final Answer:

   Typo in DataFrame capitalization -> Option A

4. Quick Check:

   Class name is DataFrame, not Dataframe [OK]

Hint: Check capitalization of DataFrame class [OK]

Common Mistakes:

• Writing Dataframe instead of DataFrame
• Ignoring case sensitivity in Python
• Assuming print() causes error

5. You have a CSV file with sales data. Which pandas function helps you load this file into a DataFrame for analysis?

hard

A. pd.load_file()

B. pd.open_csv()

C. pd.read_csv()

D. pd.import_csv()

Solution

1. Step 1: Identify pandas function for CSV files

   Pandas provides read_csv() to load CSV files into DataFrames easily.

2. Step 2: Check options for correctness

   Only pd.read_csv() is a valid pandas function. Others do not exist.

3. Final Answer:

   pd.read_csv() -> Option C

4. Quick Check:

   CSV load = pd.read_csv() [OK]

Hint: Use pd.read_csv() to load CSV files [OK]

Common Mistakes:

• Using non-existent pandas functions
• Confusing with file open methods
• Trying to load CSV without pandas