Series as labeled one-dimensional array in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a pandas Series from a list.

Pandas

import pandas as pd

s = pd.Series([1])
print(s)

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

A{10, 20, 30}

B[10, 20, 30]

C(10, 20, 30)

D'10, 20, 30'

Attempts:

3 left

💡 Hint

Common Mistakes

Using curly braces {} which create a set, not a list.

Using parentheses () which create a tuple, not a list.

Passing a string instead of a list.

The pd.Series function takes a list to create a Series. Lists are enclosed in square brackets [].

2fill in blank

medium

Complete the code to create a Series with custom labels (index).

Pandas

import pandas as pd

s = pd.Series([1, 2, 3], index=[1])
print(s)

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

A[0, 1, 2]

B(1, 2, 3)

C['a', 'b', 'c']

D{'a', 'b', 'c'}

Attempts:

3 left

💡 Hint

Common Mistakes

Using a tuple or set instead of a list for the index.

Using numbers instead of strings for labels when strings are expected.

The index parameter expects a list of labels. Use square brackets with strings like ['a', 'b', 'c'].

3fill in blank

hard

Fix the error in the code to access the value with label 'b' from the Series.

Pandas

import pandas as pd

s = pd.Series([10, 20, 30], index=['a', 'b', 'c'])
value = s[[1]]
print(value)

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

A'b'

B"b"

Cb

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using the label without quotes causing a NameError.

Using the position index instead of the label.

To access a value by label, use the label as a string inside quotes: s['b'].

4fill in blank

hard

Fill both blanks to create a Series from a dictionary and print its index labels.

Pandas

import pandas as pd

data = [1]
s = pd.Series(data)
print(s.[2])

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

A{'x': 100, 'y': 200, 'z': 300}

B[100, 200, 300]

Cindex

Dkeys

Attempts:

3 left

💡 Hint

Common Mistakes

Using a list instead of a dictionary for data.

Using keys instead of index to get labels.

A Series can be created from a dictionary. The index attribute shows the labels.

5fill in blank

hard

Fill all three blanks to create a Series with custom labels, access a value by label, and print the values as a list.

Pandas

import pandas as pd

s = pd.Series([1], index=[2])
value = s[[3]]
print(list(s.values))

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

A[5, 10, 15]

B['one', 'two', 'three']

C'two'

D['a', 'b', 'c']

Attempts:

3 left

💡 Hint

Common Mistakes

Mismatching lengths of values and index.

Accessing by position instead of label.

Not converting values to a list before printing.

Create the Series with values and labels, access the value by label 'two', and print all values as a list.

Practice

1.

What is a pandas.Series best described as?

easy

A. A two-dimensional table with rows and columns

B. A one-dimensional labeled array that can hold any data type

C. A function to perform mathematical operations

D. A method to read data from a file

Solution

1. Step 1: Understand the definition of Series

   A pandas Series is a one-dimensional array with labels called an index.

2. Step 2: Compare options with definition

   A one-dimensional labeled array that can hold any data type matches the definition exactly, others describe different pandas objects or unrelated concepts.

3. Final Answer:

   A one-dimensional labeled array that can hold any data type -> Option B

4. Quick Check:

   Series = one-dimensional labeled array [OK]

Hint: Remember: Series = 1D labeled array in pandas [OK]

Common Mistakes:

• Confusing Series with DataFrame (2D)
• Thinking Series is a function or method
• Mixing Series with file operations

2.

Which of the following is the correct way to create a pandas.Series with values [10, 20, 30] and index labels ['a', 'b', 'c']?

import pandas as pd
# Choose the correct code

easy

A. pd.Series(data=[10, 20, 30], labels=['a', 'b', 'c'])

B. pd.Series(index=[10, 20, 30], data=['a', 'b', 'c'])

C. pd.Series([10, 20, 30], index=['a', 'b', 'c'])

D. pd.Series([10, 20, 30], labels=['a', 'b', 'c'])

Solution

1. Step 1: Recall Series constructor parameters

   The Series constructor uses data as first argument and index for labels.

2. Step 2: Match options with correct parameter names

   pd.Series([10, 20, 30], index=['a', 'b', 'c']) uses correct syntax: data list and index list. Others use wrong parameter names or order.

3. Final Answer:

   pd.Series([10, 20, 30], index=['a', 'b', 'c']) -> Option C

4. Quick Check:

   Use 'index' for labels in Series constructor [OK]

Hint: Use 'index' keyword for labels when creating Series [OK]

Common Mistakes:

• Using 'labels' instead of 'index'
• Swapping data and index arguments
• Passing index as 'data' parameter

3.

What will be the output of the following code?

import pandas as pd
s = pd.Series([5, 10, 15], index=['x', 'y', 'z'])
print(s['y'])

medium

A. KeyError

B. y

C. 15

D. 10

Solution

1. Step 1: Understand Series indexing by label

   Series allows access by index label. Here, 'y' corresponds to value 10.

2. Step 2: Check the printed value

   Accessing s['y'] returns 10, so print outputs 10.

3. Final Answer:

   10 -> Option D

4. Quick Check:

   Access by label 'y' returns 10 [OK]

Hint: Access Series values by index label like dictionary keys [OK]

Common Mistakes:

• Confusing label with value
• Expecting index position access with label
• Mistaking output for error

4.

Identify the error in the following code snippet:

import pandas as pd
s = pd.Series([1, 2, 3], index=['a', 'b', 'c'])
print(s['d'])

medium

A. KeyError because 'd' is not in index

B. SyntaxError due to wrong index syntax

C. No error, prints 0

D. TypeError because index labels must be integers

Solution

1. Step 1: Check index labels in Series

   The Series has index labels 'a', 'b', 'c'. 'd' is not present.

2. Step 2: Understand what happens when accessing missing label

   Accessing s['d'] raises KeyError because label 'd' does not exist.

3. Final Answer:

   KeyError because 'd' is not in index -> Option A

4. Quick Check:

   Accessing missing label causes KeyError [OK]

Hint: Accessing missing label in Series raises KeyError [OK]

Common Mistakes:

• Expecting default 0 or None for missing label
• Confusing KeyError with SyntaxError
• Thinking index labels must be integers

5.

Given a pandas.Series s = pd.Series([100, 200, 300], index=['a', 'b', 'c']), how can you add a new element with label 'd' and value 400?

hard

A. s['d'] = 400

B. s.append({'d': 400})

C. s.add('d', 400)

D. s.insert('d', 400)

Solution

1. Step 1: Recall how to add elements to Series

   You can add a new label and value by assignment using s[label] = value.

2. Step 2: Check options for correct syntax

   s['d'] = 400 uses s['d'] = 400 which adds new element. Others are invalid or incorrect methods.

3. Final Answer:

   s['d'] = 400 -> Option A

4. Quick Check:

   Assign new label with s['label'] = value [OK]

Hint: Add new item by assigning s['new_label'] = value [OK]

Common Mistakes:

• Using non-existent methods like add or insert
• Trying to append with dict without reassignment
• Confusing Series with DataFrame methods