Jupyter Notebook best practices in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of cell execution order in Jupyter Notebook

Consider this sequence of Jupyter Notebook cells executed in order. What is the output of the last cell?

Data Analysis Python

a = 5
b = 10

# Cell 1
c = a + b

# Cell 2
c = c * 2

# Cell 3
print(c)

A 20

B 15

C SyntaxError

D 30

💡 Hint

Remember that variables keep their values across cells unless redefined.

The first cell defines c as 5 + 10 = 15. The second cell doubles c to 30. The third cell prints 30.

🧠 Conceptual

intermediate

Best practice for notebook cell length

Which of the following is the best practice regarding the length of cells in a Jupyter Notebook?

A Keep cells short and focused on a single task or idea.

B Write very long cells to avoid too many cells in the notebook.

C Combine all code into one cell for faster execution.

D Use cells only for markdown and write all code in external scripts.

💡 Hint

Think about readability and debugging ease.

Short cells focused on one task improve readability and make debugging easier.

🔧 Debug

advanced

Identify the error in this notebook cell

What error will this Jupyter Notebook cell produce when run?

Data Analysis Python

import pandas as pd

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

print(df['C'])

A NameError

B TypeError

C KeyError

D No error, prints empty column

💡 Hint

Check if the column 'C' exists in the DataFrame.

Accessing a non-existent column 'C' in a DataFrame raises a KeyError.

🚀 Application

advanced

Improving notebook reproducibility

Which practice below best improves reproducibility of a Jupyter Notebook?

A Use random seeds only in some cells.

B Include all data loading and preprocessing steps in the notebook.

C Avoid comments to keep the notebook clean.

D Run cells in any order to save time.

💡 Hint

Think about what someone else needs to run your notebook and get the same results.

Including all data loading and preprocessing ensures the notebook can be run from start to finish with consistent results.

❓ visualization

expert

Effect of inline plotting in Jupyter Notebook

What is the effect of running `%matplotlib inline` in a Jupyter Notebook?

A Plots are displayed directly below the code cells as static images.

B Plots open in a new external window.

C Plots are saved automatically to disk.

D Plots are not displayed until the notebook is exported.

💡 Hint

Consider how plots appear inside the notebook interface.

The `%matplotlib inline` magic command makes plots appear inside the notebook below the code cells as static images.