duplicated() for finding duplicates in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find duplicate rows in the DataFrame df.

Pandas

duplicates = df.[1]()

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Aduplicated

Bfillna

Cisnull

Ddropna

Attempts:

3 left

💡 Hint

Common Mistakes

Using dropna() instead of duplicated()

Using isnull() which checks for missing values

The duplicated() method returns a boolean Series marking duplicate rows as True.

2fill in blank

medium

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

Pandas

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

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A'Name'

B'Age'

C'Score'

D'City'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name in subset

Not passing the column name as a string

The subset parameter specifies columns to check for duplicates. Here, we check duplicates based on 'Name'.

3fill in blank

hard

Fix the error in the code to mark duplicate rows in df, keeping the first occurrence.

Pandas

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

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A'last'

BFalse

C'first'

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Using boolean True instead of string 'first'

Using None which is invalid here

The keep parameter accepts 'first', 'last', or False. 'first' marks duplicates except the first occurrence.

4fill in blank

hard

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

Pandas

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

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition

Using 'word' instead of 'len(word)' for the value

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

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 4 letters.

Pandas

result = {{ [1]: [2] for w in words if len(w) [3] 4 }}

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Aw.upper()

Blen(w)

C>

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'w' instead of 'w.upper()' for keys

Using '<' instead of '>' in the condition

This comprehension creates a dictionary with uppercase words as keys and their lengths as values, filtering words longer than 4.