Word frequency analysis in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to split the text into words.

Data Analysis Python

text = "Data science is fun and data is powerful."
words = text.[1]()

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Areplace

Bjoin

Cstrip

Dsplit

Attempts:

3 left

💡 Hint

Common Mistakes

Using join() instead of split()

Using replace() which changes characters but does not split

Using strip() which only removes whitespace from ends

The split() method breaks the text into a list of words separated by spaces.

2fill in blank

medium

Complete the code to count how many times each word appears.

Data Analysis Python

from collections import [1]
counter = [1](words)

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AOrderedDict

Bdefaultdict

CCounter

Dnamedtuple

Attempts:

3 left

💡 Hint

Common Mistakes

Using defaultdict which needs manual counting

Using OrderedDict which keeps order but does not count

Using namedtuple which is for fixed data structures

Counter from collections counts the frequency of each item in a list.

3fill in blank

hard

Fix the error in the code to get the most common word and its count.

Data Analysis Python

most_common_word, count = counter.[1](1)[0]

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Amostcommon

Bmost_common

Ccommon_most

Dcommon

Attempts:

3 left

💡 Hint

Common Mistakes

Misspelling the method name

Using a method that does not exist

Trying to access attributes instead of calling a method

The correct method name is most_common() which returns a list of tuples with word and count.

4fill in blank

hard

Fill both blanks to create a dictionary of words longer than 3 letters and their counts.

Data Analysis Python

filtered_counts = {word: counter[word] for word in counter if [1](word) [2] 3}

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Alen

B>

C<

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using count instead of len for word length

Using < instead of > for filtering

Not calling len as a function

We use len(word) to get word length and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a sorted list of words by frequency in descending order.

Data Analysis Python

sorted_words = sorted(counter.items(), key=lambda [1]: [2][[3]], reverse=True)

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Ax

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 instead of 1 to sort by word instead of count

Using a different variable name inconsistently

Forgetting reverse=True for descending order

The lambda function takes each item x and sorts by the second element x[1] which is the count. reverse=True sorts descending.