Creating Series from list and dictionary in Pandas - Practice Exercises

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Series created from list with index

What is the output of this code snippet?

Pandas

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

A 10

B KeyError

C 30

D 20

💡 Hint

Remember that the index labels are used to access values in a Series.

The Series is created with index labels 'a', 'b', 'c'. Accessing s['b'] returns the value 20.

❓ data_output

intermediate

Length of Series created from dictionary

How many items are in the Series created from this dictionary?

Pandas

import pandas as pd
d = {'x': 1, 'y': 2, 'z': 3}
s = pd.Series(d)
print(len(s))

A 3

B 2

C 1

D 0

💡 Hint

Each key-value pair in the dictionary becomes one item in the Series.

The dictionary has 3 key-value pairs, so the Series has length 3.

🔧 Debug

advanced

Error raised when creating Series with mismatched index

What error does this code raise?

Pandas

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

A ValueError: Length of passed values is 2, index implies 3

B TypeError: unsupported operand type(s)

C KeyError: 'c'

D No error, creates Series with NaN

💡 Hint

Check if the length of data matches the length of the index.

The data list has length 2 but the index has length 3, causing a ValueError.

🧠 Conceptual

advanced

Behavior of Series when dictionary keys are not strings

What will be the index of the Series created from this dictionary?

Pandas

import pandas as pd
d = {1: 'a', 2: 'b', 3: 'c'}
s = pd.Series(d)
print(s.index.tolist())

A ['1', '2', '3']

B [1, 2, 3]

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

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

💡 Hint

Dictionary keys become the index labels as they are.

The Series index uses the dictionary keys as labels, so the index is [1, 2, 3].

🚀 Application

expert

Creating Series with partial index from dictionary

Given the dictionary and index below, what is the output of the Series?

Pandas

import pandas as pd
d = {'a': 100, 'b': 200, 'c': 300}
index = ['a', 'c', 'd']
s = pd.Series(d, index=index)
print(s)

A KeyError: 'd'

B

a    100
b    200
c    300
d    NaN
dtype: float64

C

a    100.0
c    300.0
d      NaN
dtype: float64

D

a    100
c    300
d    0
dtype: int64

💡 Hint

When index has labels not in dictionary keys, pandas fills with NaN.

The Series uses the given index. 'd' is missing in dictionary, so its value is NaN.

Practice

1. What happens when you create a pandas Series from a dictionary?

easy

A. The dictionary keys become the Series index labels automatically.

B. The dictionary values become the index labels.

C. The Series will have numeric index ignoring the dictionary keys.

D. It raises an error because Series cannot be created from dictionaries.

Solution

1. Step 1: Understand Series creation from dictionary

   When creating a Series from a dictionary, pandas uses the dictionary keys as the index labels.

2. Step 2: Identify the role of dictionary keys and values

   The dictionary values become the data in the Series, and keys become the index labels automatically.

3. Final Answer:

   The dictionary keys become the Series index labels automatically. -> Option A

4. Quick Check:

   Dictionary keys = index labels [OK]

Hint: Keys become index labels automatically when using dict [OK]

Common Mistakes:

• Confusing keys with values as index
• Thinking Series always uses numeric index
• Assuming error occurs with dict input

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

easy

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

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

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

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

Solution

1. Step 1: Recall Series constructor parameters

   The correct parameters are data first, then index for labels.

2. Step 2: Match correct syntax

   pd.Series([10, 20, 30], index=['a', 'b', 'c']) uses pd.Series([10, 20, 30], index=['a', 'b', 'c']) which is correct syntax.

3. Final Answer:

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

4. Quick Check:

   Use index= for labels in Series constructor [OK]

Hint: Use index= for labels when creating Series from list [OK]

Common Mistakes:

• Using labels= instead of index=
• Swapping data and index parameters
• Passing index before data

3. What is the output of this code?

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

medium

A. 5

B. 10

C. 15

D. KeyError

Solution

1. Step 1: Create Series from dictionary

   The Series has index labels 'x', 'y', 'z' with values 5, 10, 15 respectively.

2. Step 2: Access value by index label 'y'

   Accessing s['y'] returns the value 10.

3. Final Answer:

   10 -> Option B

4. Quick Check:

   s['y'] = 10 [OK]

Hint: Access Series by index label to get corresponding value [OK]

Common Mistakes:

• Confusing index label with position
• Expecting numeric index access
• Mistaking value for key

4. Identify the error in this code snippet:

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

medium

A. TypeError because index must be integers.

B. SyntaxError due to missing parentheses.

C. No error; code runs fine.

D. Index length does not match data length causing ValueError.

Solution

1. Step 1: Check data and index lengths

   Data has 3 elements but index has only 2 labels.

2. Step 2: Understand pandas behavior

   Pandas raises ValueError if index length does not match data length.

3. Final Answer:

   Index length does not match data length causing ValueError. -> Option D

4. Quick Check:

   Data length != index length causes ValueError [OK]

Hint: Ensure index length matches data length when creating Series [OK]

Common Mistakes:

• Assuming pandas auto-adjusts index length
• Confusing ValueError with SyntaxError
• Thinking index must be integers

5. You have a dictionary {'a': 1, 'b': 0, 'c': 3, 'd': 0}. How do you create a pandas Series from it that only includes keys with values greater than zero?

hard

A. pd.Series(d).loc[d > 0]

B. pd.Series(d).filter(lambda x: x > 0)

C. pd.Series({k: v for k, v in d.items() if v > 0})

D. pd.Series(d).dropna()

Solution

1. Step 1: Filter dictionary items with values > 0

   Use dictionary comprehension to keep only items where value > 0.

2. Step 2: Create Series from filtered dictionary

   Pass the filtered dictionary to pd.Series to create the Series with desired keys and values.

3. Final Answer:

   pd.Series({k: v for k, v in d.items() if v > 0}) -> Option C

4. Quick Check:

   Filter dict first, then create Series [OK]

Hint: Filter dict before Series creation to exclude unwanted keys [OK]

Common Mistakes:

• Using filter() which is not a Series method
• Using dropna() which removes NaNs, not zeros
• Trying to index Series with dict directly