Jupyter Notebook best practices in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a markdown cell with a title in Jupyter Notebook.

Data Analysis Python

# [1] This is a title

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

Adef

Bprint

Cimport

D#

Attempts:

3 left

💡 Hint

Common Mistakes

Using print instead of markdown syntax.

Trying to write code instead of markdown.

In Jupyter Notebook, markdown cells use # to create titles.

2fill in blank

medium

Complete the code to import pandas library in a Jupyter Notebook cell.

Data Analysis Python

[1] pandas as pd

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

Aexport

Binclude

Cimport

Drequire

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'export' or 'require' which are not Python keywords.

Forgetting to alias pandas as pd.

Use import to bring pandas into your notebook.

3fill in blank

hard

Fix the error in the code to display the first 5 rows of a DataFrame named df.

Data Analysis Python

df.[1]()

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

Ashow

Bhead

Cprint

Ddisplay

Attempts:

3 left

💡 Hint

Common Mistakes

Using print() which prints the whole DataFrame.

Using show() which is not a pandas method.

The head() method shows the first 5 rows of a DataFrame.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Data Analysis Python

{word: [1] for word in words if [2]

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Using the word in the condition instead of its length.

The dictionary comprehension maps each word to its length using len(word). The condition filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their counts only if count is greater than 0.

Data Analysis Python

{ [1]: [2] for [3], [2] in data.items() if [2] > 0 }

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

Aword.upper()

Bcount

Cword

Ddata

Attempts:

3 left

💡 Hint

Common Mistakes

Using the variable 'data' as a key instead of 'word.upper()'.

Mixing up the variable names in the loop.

The comprehension maps each word in uppercase (word.upper()) to its count (count) only if the count is greater than 0. The loop unpacks word and count from data.items().