shape for dimensions in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

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

The shape attribute shows the number of rows and columns in the DataFrame as a tuple: (rows, columns).

beginner

How can you get the number of rows in a pandas DataFrame using shape?

Use df.shape[0] to get the number of rows in the DataFrame df.

beginner

How do you find the number of columns in a pandas DataFrame using shape?

Use df.shape[1] to get the number of columns in the DataFrame df.

beginner

What type of value does shape return in pandas?

shape returns a tuple of two integers representing (number of rows, number of columns).

beginner

If a DataFrame df has df.shape == (100, 5), what does it mean?

It means df has 100 rows and 5 columns.

What does df.shape return for a pandas DataFrame?

A A tuple with (rows, columns)

B A list of column names

C The total number of cells

D The data types of columns

df.shape returns a tuple showing the number of rows and columns.

How do you get the number of columns from df.shape?

A <code>df.shape[0]</code>

B <code>df.shape[1]</code>

C <code>len(df.shape)</code>

D <code>df.columns</code>

The second element of the tuple (df.shape[1]) is the number of columns.

If df.shape is (50, 10), how many rows does df have?

A 50

B 500

C 60

D 10

The first number in the tuple is the number of rows.

Which of these is NOT true about df.shape?

A It returns a tuple

B It shows the DataFrame size

C It returns the data types of columns

D It has two elements

df.shape does not return data types; it returns the dimensions.

What Python type is returned by df.shape?

A Integer

B List

C Dictionary

D Tuple

df.shape returns a tuple with two integers.

Explain what the shape attribute of a pandas DataFrame represents and how to use it to find the number of rows and columns.

Think of shape as the size of a table: rows first, then columns.

Describe a real-life example where knowing the shape of your data helps in data analysis.

Imagine you just opened a spreadsheet and want to know how big it is.

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