Series indexing and selection in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the element at index 2 from the Series.

Data Analysis Python

import pandas as pd
s = pd.Series([10, 20, 30, 40])
value = s[1]

Drag options to blanks, or click blank then click option'

A[2]

B.loc[2]

C.iloc[2]

D[3]

Attempts:

3 left

💡 Hint

Common Mistakes

Using .loc instead of square brackets for positional selection

Using the wrong index number

Using square brackets with the index number selects the element at that position in the Series.

2fill in blank

medium

Complete the code to select elements with labels 1 and 3 using .loc.

Data Analysis Python

import pandas as pd
s = pd.Series([100, 200, 300, 400], index=[0, 1, 2, 3])
subset = s[1]

Drag options to blanks, or click blank then click option'

A[[1, 3]]

B.loc[[1, 3]]

C.iloc[[1, 3]]

D[1, 3]

Attempts:

3 left

💡 Hint

Common Mistakes

Using .iloc instead of .loc for label-based selection

Not using double brackets for list selection

.loc is used to select elements by their index labels. Here, labels 1 and 3 are selected.

3fill in blank

hard

Fix the error in the code to select the element at position 1 using .iloc.

Data Analysis Python

import pandas as pd
s = pd.Series([5, 10, 15])
value = s[1]

Drag options to blanks, or click blank then click option'

A.iloc[1]

B.loc[1]

C[1]

D[[1]]

Attempts:

3 left

💡 Hint

Common Mistakes

Using .loc instead of .iloc for position selection

Using double brackets which returns a Series instead of a scalar

.iloc selects by integer position. Using .iloc[1] correctly gets the second element.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

Data Analysis Python

words = ['apple', 'bat', 'carrot', 'dog']
lengths = {word: [1] for word in words if [2]

Drag options to blanks, or click blank then click option'

Alen(word)

Blen(word) > 3

Cword

Dlen(word) < 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length

Using the wrong condition for filtering

The dictionary comprehension maps each word to its length if the word length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values greater than 0.

Data Analysis Python

data = {'a': 1, 'b': -2, 'c': 3}
result = [1]: [2] for k, v in data.items() if v [3] 0}

Drag options to blanks, or click blank then click option'

Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper()

Using '<' instead of '>' in the condition

Using keys or values incorrectly in the comprehension

The dictionary comprehension uses uppercase keys, keeps values, and filters values greater than zero.

Practice

1. What does series['a'] do in a pandas Series with index labels?

easy

A. Returns a slice from start to label 'a'

B. Selects the value at label 'a' in the Series

C. Selects the value at position 0 in the Series

D. Raises an error because 'a' is not a position

Solution

1. Step 1: Understand label-based indexing

   Using series['a'] accesses the value at the index label 'a', not position.

2. Step 2: Differentiate label vs position

   Label 'a' is a named index, so it returns the value at that label.

3. Final Answer:

   Selects the value at label 'a' in the Series -> Option B

4. Quick Check:

   Label indexing = value at label [OK]

Hint: Use labels inside quotes to get values by label [OK]

Common Mistakes:

• Confusing label with position indexing
• Thinking 'a' is a position index
• Expecting a slice instead of single value

2. Which of these is the correct syntax to select multiple labels 'a' and 'c' from a Series named ser?

easy

A. ser.loc[['a', 'c']]

B. ser['a', 'c']

C. ser.loc['a', 'c']

D. ser.iloc[['a', 'c']]

Solution

1. Step 1: Understand selection of multiple labels

   To select multiple labels, use loc with a list of labels inside double brackets.

2. Step 2: Check syntax correctness

   ser.loc[['a', 'c']] is correct; distractors B and C use tuples (KeyError), D uses iloc which expects positions (TypeError).

3. Final Answer:

   ser.loc[['a', 'c']] -> Option A

4. Quick Check:

   Use loc with list for multiple labels [OK]

Hint: Use ser.loc[[labels]] to select multiple labels [OK]

Common Mistakes:

• Using single brackets for multiple labels
• Omitting loc when selecting multiple labels
• Passing labels as separate arguments instead of a list

3. Given the Series:

import pandas as pd
ser = pd.Series([10, 20, 30, 40], index=['a', 'b', 'c', 'd'])
print(ser['b':'d'])

What is the output?

medium

A. b 20
c 30
d 40
dtype: int64

B. b 20
c 30
dtype: int64

C. 20
30
40

D. 20
30

Solution

1. Step 1: Understand label slicing in Series

   Label slicing with ser['b':'d'] includes both start and end labels.

2. Step 2: Identify values for labels 'b' to 'd'

   Labels 'b', 'c', and 'd' correspond to values 20, 30, and 40 respectively.

3. Final Answer:

   b 20 c 30 d 40 dtype: int64 -> Option A

4. Quick Check:

   Label slice includes end label [OK]

Hint: Label slices include the end label [OK]

Common Mistakes:

• Excluding the end label in slice
• Confusing label slicing with position slicing
• Expecting only values without index labels

4. What is wrong with this code snippet?

import pandas as pd
ser = pd.Series([1, 2, 3], index=['x', 'y', 'z'])
print(ser[1:2])

Why might this cause confusion?

medium

A. It raises a KeyError because 1 and 3 are not labels

B. It returns a single value instead of a slice

C. It returns values for labels 'y' and 'z' inclusive

D. It slices by position, excluding index label 'z'

Solution

1. Step 1: Understand position slicing in Series

   Using ser[1:2] slices by position, not label, and excludes the end position.

2. Step 2: Identify slice range and output

   Position 1 (inclusive) to 2 (exclusive) corresponds to label 'y' (position 1), excluding position 2 ('z').

3. Final Answer:

   It slices by position, excluding index label 'z' -> Option D

4. Quick Check:

   Position slices exclude end position [OK]

Hint: Position slices exclude the end index [OK]

Common Mistakes:

• Expecting label slicing with integer slice
• Thinking slice includes end position
• Confusing KeyError with slicing behavior

5. You have a Series ser with index labels ['a', 'b', 'c', 'd', 'e'] and values [5, 10, 15, 20, 25]. How do you select all values greater than 10 using Series indexing and selection?

hard

A. ser[ser.index > 10]

B. ser.index[ser > 10]

C. ser[ser > 10]

D. ser.loc[ser.index > 10]

Solution

1. Step 1: Use boolean indexing on Series values

   Comparing ser > 10 creates a boolean mask for values greater than 10.

2. Step 2: Apply boolean mask to Series

   Using ser[ser > 10] selects values where the mask is True.

3. Final Answer:

   ser[ser > 10] -> Option C

4. Quick Check:

   Boolean mask on values selects correct subset [OK]

Hint: Use ser[ser > value] to filter by value condition [OK]

Common Mistakes:

• Trying to filter by index values instead of data values
• Using loc with boolean mask on index instead of values
• Confusing index labels with values in condition