describe() for statistics in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to get basic statistics of the DataFrame.

Data Analysis Python

stats = df.[1]()

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

Atail

Binfo

Cdescribe

Dhead

Attempts:

3 left

💡 Hint

Common Mistakes

Using info() instead of describe() which shows data types, not statistics.

Using head() or tail() which show rows, not statistics.

The describe() method provides basic statistics like mean, count, min, max, and quartiles for numerical columns.

2fill in blank

medium

Complete the code to include statistics for all columns, including non-numeric ones.

Data Analysis Python

stats_all = df.describe([1]='all')

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

Ainclude

Bexclude

Cnumeric_only

Dall

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'all=True' which is not a valid argument.

Using 'numeric_only=True' which limits to numeric columns only.

The include='all' argument tells describe() to include all columns, not just numeric ones.

3fill in blank

hard

Fix the error in the code to get statistics only for numeric columns.

Data Analysis Python

num_stats = df.describe([1]=True)

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

Anumeric_only

Bexclude

Cinclude

Dall

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'include=True' which includes all columns.

Using 'all=True' which is invalid.

To get statistics only for numeric columns, use numeric_only=True. This excludes non-numeric columns.

4fill in blank

hard

Fill both blanks to create a dictionary of statistics for words longer than 3 letters.

Data Analysis Python

lengths = {word: [1] for word in words if len(word) [2] 3 }

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

Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which selects shorter words.

Using 'word' instead of 'len(word)' which stores the word itself.

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

5fill in blank

hard

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

Data Analysis Python

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

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'k' instead of 'k.upper()' which does not change the key case.

Using '<' instead of '>' which filters values less than zero.

This comprehension creates a dictionary with keys as uppercase strings and values only if they are greater than zero.