shape for dimensions in Pandas - Mini Project: Build & Apply

Understanding DataFrame Shape for Dimensions

📖 Scenario: Imagine you work in a small bookstore. You have a list of books with details like title, author, and price. You want to understand how many books you have and how many details are recorded for each book.

🎯 Goal: You will create a pandas DataFrame with book details and then find out its shape, which tells you the number of rows and columns.

📋 What You'll Learn

Create a pandas DataFrame with exact book data

Create a variable to store the DataFrame shape

Use the shape attribute to get dimensions

Print the shape to see rows and columns

💡 Why This Matters

🌍 Real World

Knowing the shape of data helps you understand how much information you have and how it is organized, which is important before analysis.

💼 Career

Data scientists and analysts often check data dimensions to plan cleaning, visualization, and modeling steps.

1

Create the DataFrame with book details

Import pandas as pd and create a DataFrame called books with these exact entries: columns 'Title', 'Author', 'Price' and rows: 'The Alchemist', 'Paulo Coelho', 10.99, '1984', 'George Orwell', 8.99, 'Python 101', 'Michael Driscoll', 15.50.

Pandas

# Import pandas and create the DataFrame called books
# Your code here

Hint

Use pd.DataFrame with a dictionary where keys are column names and values are lists of column data.

2

Create a variable to store the DataFrame shape

Create a variable called dimensions and set it to the shape of the books DataFrame using the shape attribute.

Pandas

import pandas as pd
books = pd.DataFrame({
    'Title': ['The Alchemist', '1984', 'Python 101'],
    'Author': ['Paulo Coelho', 'George Orwell', 'Michael Driscoll'],
    'Price': [10.99, 8.99, 15.50]
})
# Create variable dimensions to store books shape
# Your code here

Hint

Use books.shape to get a tuple with rows and columns.

3

Extract number of rows and columns

Create two variables called num_rows and num_columns. Set num_rows to the first value of dimensions and num_columns to the second value of dimensions.

Pandas

import pandas as pd
books = pd.DataFrame({
    'Title': ['The Alchemist', '1984', 'Python 101'],
    'Author': ['Paulo Coelho', 'George Orwell', 'Michael Driscoll'],
    'Price': [10.99, 8.99, 15.50]
})
dimensions = books.shape
# Extract num_rows and num_columns from dimensions
# Your code here

Hint

The shape attribute returns a tuple: first is rows, second is columns.

4

Print the number of rows and columns

Print the values of num_rows and num_columns separated by a space.

Pandas

import pandas as pd
books = pd.DataFrame({
    'Title': ['The Alchemist', '1984', 'Python 101'],
    'Author': ['Paulo Coelho', 'George Orwell', 'Michael Driscoll'],
    'Price': [10.99, 8.99, 15.50]
})
dimensions = books.shape
num_rows = dimensions[0]
num_columns = dimensions[1]
# Print num_rows and num_columns separated by a space
# Your code here

Hint

Use print(num_rows, num_columns) to show the shape.

Practice

1. What does the shape attribute of a pandas DataFrame tell you?

easy

A. The data types of each column

B. The summary statistics of the data

C. The first few rows of the DataFrame

D. The number of rows and columns as a tuple (rows, columns)

Solution

1. Step 1: Understand what shape returns

   The shape attribute gives the size of the DataFrame as a tuple showing rows and columns.

2. Step 2: Compare options with this definition

   Only The number of rows and columns as a tuple (rows, columns) correctly describes shape as (rows, columns).

3. Final Answer:

   The number of rows and columns as a tuple (rows, columns) -> Option D

4. Quick Check:

   shape = (rows, columns) [OK]

Hint: Remember shape shows (rows, columns) size [OK]

Common Mistakes:

• Confusing shape with data types
• Thinking shape shows data preview
• Mixing shape with summary statistics

2. Which of the following is the correct way to get the shape of a pandas DataFrame named df?

easy

A. df.shape()

B. df.shape

C. df.get_shape()

D. shape(df)

Solution

1. Step 1: Recall how to access attributes in pandas

   The shape is an attribute, not a method, so no parentheses are used.

2. Step 2: Check each option

   df.shape uses df.shape correctly without parentheses. Others are incorrect syntax.

3. Final Answer:

   df.shape -> Option B

4. Quick Check:

   Use attribute without () for shape [OK]

Hint: Use attribute without parentheses for shape [OK]

Common Mistakes:

• Adding parentheses like a function call
• Using non-existent methods like get_shape()
• Trying to call shape as a standalone function

3. Given the following code:

import pandas as pd
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)
print(df.shape)

What will be the output?

medium

A. (3, 2)

B. (2, 3)

C. [3, 2]

D. Error

Solution

1. Step 1: Understand the DataFrame structure

   The dictionary has 2 keys (columns) and each key has 3 values (rows).

2. Step 2: Determine the shape

   So the DataFrame has 3 rows and 2 columns, shape is (3, 2).

3. Final Answer:

   (3, 2) -> Option A

4. Quick Check:

   Rows = 3, Columns = 2 [OK]

Hint: Count rows then columns for shape tuple [OK]

Common Mistakes:

• Swapping rows and columns order
• Using list brackets instead of tuple
• Expecting an error from correct code

4. You run this code:

import pandas as pd
df = pd.DataFrame({'X': [1, 2], 'Y': [3, 4]})
print(df.shape())

What is the problem?

medium

A. Column names are invalid

B. DataFrame is empty

C. Using parentheses with shape causes an error

D. Missing import statement

Solution

1. Step 1: Identify how shape is accessed

   shape is an attribute, not a method, so it should not have parentheses.

2. Step 2: Understand the error cause

   Calling df.shape() tries to call a tuple as a function, causing a TypeError.

3. Final Answer:

   Using parentheses with shape causes an error -> Option C

4. Quick Check:

   Access shape without () to avoid error [OK]

Hint: Don't add () after shape attribute [OK]

Common Mistakes:

• Treating shape like a function
• Assuming empty DataFrame causes error
• Ignoring import errors

5. You have a pandas Series s = pd.Series([10, 20, 30, 40]). What will s.shape return?

hard

A. (4,)

B. (4, 1)

C. 4

D. Error

Solution

1. Step 1: Understand Series shape

   A pandas Series is one-dimensional, so its shape is a tuple with one element: the number of items.

2. Step 2: Check the length of the Series

   There are 4 elements, so shape is (4,).

3. Final Answer:

   (4,) -> Option A

4. Quick Check:

   Series shape is single-element tuple (length,) [OK]

Hint: Series shape is a one-item tuple with length [OK]

Common Mistakes:

• Expecting a 2D shape tuple
• Returning just an integer instead of tuple
• Thinking shape causes error on Series