Duplicates on specific columns in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find duplicate rows based on the 'Name' column.

Pandas

duplicates = df.duplicated(subset=[1])

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

A['Name']

B'Age'

C'Salary'

D['City']

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string instead of a list for subset.

Checking duplicates without specifying subset.

The duplicated() method checks for duplicate rows. Using subset=['Name'] tells pandas to look for duplicates only in the 'Name' column.

2fill in blank

medium

Complete the code to drop duplicate rows based on 'Name' and 'City' columns, keeping the first occurrence.

Pandas

df_unique = df.drop_duplicates(subset=[1], keep='first')

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

A'Name'

B['Name', 'City']

C'City'

D['Age', 'Salary']

Attempts:

3 left

💡 Hint

Common Mistakes

Using a single string instead of a list for subset.

Not specifying the keep parameter.

The drop_duplicates() method removes duplicate rows. Specifying subset=['Name', 'City'] means duplicates are checked only on these two columns.

3fill in blank

hard

Fix the error in the code to find duplicates based on 'Age' column.

Pandas

duplicates = df.duplicated(subset=[1])

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

AAge

B'Age'

C'age'

D['Age']

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a string instead of a list.

Using a variable without quotes.

The subset parameter requires a list of column names. Using ['Age'] is correct. A string alone or a variable without quotes causes errors.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, but only for words longer than 4 characters.

Pandas

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

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Alen(word)

Blen(word) > 4

Cword > 4

Dword.length()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word > 4 instead of length comparison.

Using word.length() which is not valid in Python.

The dictionary comprehension uses len(word) to get the length. The condition len(word) > 4 filters words longer than 4 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase words as keys and their lengths as values, only for words longer than 3 characters.

Pandas

result = [1]: [2] for word in words if [3]

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Aword.upper()

Blen(word)

Clen(word) > 3

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.lower() instead of uppercase.

Not filtering words by length.

The dictionary keys are uppercase words using word.upper(). Values are lengths with len(word). The condition filters words longer than 3 characters.