DataFrame structure (index, columns, values) in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ query_result

intermediate

What is the output of this DataFrame index query?

Given the DataFrame df below, what will df.index return?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35]
})

result = df.index

A None

B Index(['Alice', 'Bob', 'Charlie'], dtype='object')

C Index(['Name', 'Age'], dtype='object')

D RangeIndex(start=0, stop=3, step=1)

💡 Hint

The index represents the row labels, which by default are numbers starting at zero.

By default, pandas assigns a RangeIndex starting at 0 for rows if no index is specified.

❓ query_result

intermediate

What does df.columns return for this DataFrame?

Given the DataFrame df below, what will df.columns output?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'City': ['Paris', 'London', 'Berlin'],
    'Population': [2148000, 8982000, 3769000]
})

result = df.columns

A ['Paris', 'London', 'Berlin']

B Index(['City', 'Population'], dtype='object')

C RangeIndex(start=0, stop=3, step=1)

D ['City', 'Population', 'Country']

💡 Hint

Columns represent the names of the data fields in the DataFrame.

The columns attribute returns the labels of the columns as an Index object.

❓ query_result

advanced

What is the output of df.values for this DataFrame?

Given the DataFrame df below, what will df.values return?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'Product': ['Pen', 'Pencil'],
    'Price': [1.5, 0.5]
})

result = df.values

A

[['Pen' 1.5]
 ['Pencil' 0.5]]

B

[['Product' 'Price']
 ['Pen' 1.5]
 ['Pencil' 0.5]]

C [['Pen', 1.5], ['Pencil', 0.5]]

D Index(['Pen', 'Pencil'], dtype='object')

💡 Hint

Values returns the data as a 2D array without the index or columns labels.

df.values returns the underlying data as a numpy array of lists representing rows.

🧠 Conceptual

advanced

Which statement about DataFrame structure is true?

Select the correct statement about the structure of a pandas DataFrame.

A The index labels the rows, and columns label the columns.

B Columns are always numeric and index is always string.

C Values include the index and columns labels.

D The index labels the columns, and columns label the rows.

💡 Hint

Think about what index and columns represent in a table.

The index labels the rows, and columns label the columns. Values are the data inside.

🔧 Debug

expert

Why does this code raise an error when accessing DataFrame values?

Consider this code snippet:

import pandas as pd

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

result = df.values[0]['A']

Why does this raise an error?

A Because df.values returns a numpy array, which does not support string indexing.

B Because df.values returns a dictionary, and dictionaries cannot be indexed by integers.

C Because the DataFrame has no column named 'A'.

D Because the DataFrame is empty.

💡 Hint

Check the type of object returned by df.values and how it can be indexed.

df.values returns a numpy array of the data, so indexing by string like ['A'] is invalid.

Practice

1. Which part of a DataFrame represents the labels for the rows?

easy

A. Values

B. Columns

C. Index

D. Cells

Solution

1. Step 1: Understand DataFrame parts

   A DataFrame has three main parts: index (row labels), columns (column names), and values (data).

2. Step 2: Identify row labels

   The row labels are called the index, which helps identify each row uniquely.

3. Final Answer:

   Index -> Option C

4. Quick Check:

   Row labels = Index [OK]

Hint: Rows are labeled by the index in a DataFrame [OK]

Common Mistakes:

• Confusing columns with index
• Thinking values are labels
• Mixing cells with index

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

easy

A. df.columns

B. df.index

C. df.values

D. df.names

Solution

1. Step 1: Recall DataFrame attributes

   To get column names, use the columns attribute of the DataFrame.

2. Step 2: Match correct syntax

   The correct syntax is df.columns. Other options refer to rows or data.

3. Final Answer:

   df.columns -> Option A

4. Quick Check:

   Columns = df.columns [OK]

Hint: Use df.columns to get column names quickly [OK]

Common Mistakes:

• Using df.index for columns
• Trying df.names which doesn't exist
• Using df.values for columns

3. Given the DataFrame df below:

   A  B  C
0  1  4  7
1  2  5  8
2  3  6  9

What will df.values[1, 2] return?

medium

A. 5

B. 2

C. 6

D. 8

Solution

1. Step 1: Understand DataFrame values and indexing

   df.values returns the data as a 2D array. The first index is the row, the second is the column.

2. Step 2: Locate the value at row 1, column 2

   Row 1 is the second row: [2, 5, 8]. Column 2 is the third column, value 8.

3. Final Answer:

   8 -> Option D

4. Quick Check:

   df.values[1, 2] = 8 [OK]

Hint: Remember indexing starts at 0 for rows and columns [OK]

Common Mistakes:

• Mixing row and column indexes
• Using df.iloc instead of df.values
• Off-by-one errors in indexing

4. What is wrong with this code to get the row labels of a DataFrame df?

row_labels = df.values

medium

A. It returns an empty list

B. It returns the data values, not the row labels

C. It returns the column names instead

D. It causes a syntax error

Solution

1. Step 1: Understand what df.values returns

   df.values returns the data inside the DataFrame as a numpy array, not the row labels.

2. Step 2: Identify correct attribute for row labels

   Row labels are stored in df.index, not df.values.

3. Final Answer:

   It returns the data values, not the row labels -> Option B

4. Quick Check:

   df.values ≠ row labels [OK]

Hint: Use df.index for rows, not df.values [OK]

Common Mistakes:

• Confusing df.values with df.index
• Expecting df.values to give labels
• Using wrong attribute names

5. You have a DataFrame df with custom row labels ["a", "b", "c"] and columns ["X", "Y"]. Which code correctly extracts the data values as a 2D array?

hard

A. df.values

B. df.index

C. df.columns

D. df.data

Solution

1. Step 1: Recall DataFrame parts

   Index holds row labels, columns hold column names, and values hold the actual data.

2. Step 2: Identify correct attribute for data values

   To get the data as a 2D array, use df.values. Other options do not return data values.

3. Final Answer:

   df.values -> Option A

4. Quick Check:

   Data values = df.values [OK]

Hint: Use df.values to get data regardless of labels [OK]

Common Mistakes:

• Using df.index or df.columns for data
• Trying df.data which doesn't exist
• Confusing labels with values