Why indexing matters in Pandas - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the first row of the DataFrame using .iloc.

Pandas

first_row = df.[1][0]

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

Ailoc

Bat

Cloc

Diat

Attempts:

3 left

💡 Hint

Common Mistakes

Using loc instead of iloc causes errors if index labels are not integers.

Using at or iat requires scalar access, not slicing.

The iloc method selects rows by integer position. Here, df.iloc[0] gets the first row.

2fill in blank

medium

Complete the code to set the 'id' column as the DataFrame index.

Pandas

df = df.[1]('id')

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

Aset_index

Brename

Creset_index

Ddrop

Attempts:

3 left

💡 Hint

Common Mistakes

Using reset_index removes the current index instead of setting a new one.

Using drop or rename does not change the index.

The set_index method sets a column as the DataFrame index.

3fill in blank

hard

Fix the error in the code to select rows where the index is greater than 5.

Pandas

filtered = df[df.index [1] 5]

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A<=

B==

C>

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' selects only index equal to 5, not greater.

Using '<=' selects index less than or equal to 5.

To filter rows with index greater than 5, use the '>' operator.

4fill in blank

hard

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

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 '<' filters words shorter than 3 characters.

Using 'word' instead of len(word) gives the word itself, not its length.

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 keys and values greater than zero.

Pandas

result = [1]: [2] for k, v in data.items() if v [3] 0}

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Ak.upper()

Bv

C>

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() creates lowercase keys instead of uppercase.

Using '<' or '!=' in the condition filters wrong values.

This dictionary comprehension creates keys as uppercase strings and includes only items with values greater than zero.