Forward fill and backward fill in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to fill missing values forward in the DataFrame column.

Data Analysis Python

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

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Afillna

Bbfill

Cffill

Ddropna

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'bfill' which fills backward instead of forward.

Using 'fillna' without specifying method.

Using 'dropna' which removes missing values instead of filling.

The ffill() method fills missing values by propagating the last valid observation forward.

2fill in blank

medium

Complete the code to fill missing values backward in the DataFrame column.

Data Analysis Python

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

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

Abfill

Bdropna

Cffill

Dfillna

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ffill' which fills forward instead of backward.

Using 'fillna' without specifying method.

Using 'dropna' which removes missing values instead of filling.

The bfill() method fills missing values by using the next valid observation backward.

3fill in blank

hard

Fix the error in the code to forward fill missing values in the DataFrame.

Data Analysis Python

df['pressure'] = df['pressure'].fillna(method=[1])

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

A'ffill'

B'forward'

C'backward'

D'bfill'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'forward' which is not a valid method argument.

Using 'backward' which fills backward.

Using 'bfill' which is backward fill.

The correct method argument for forward fill in fillna() is 'ffill'.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

Data Analysis Python

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

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of length.

Using the word in condition instead of length check.

Using incorrect comparison operators.

The dictionary comprehension maps each word to its length using len(word). The condition filters words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their values only if the value is greater than 0.

Data Analysis Python

{ [1]: [2] for [3], [2] in data.items() if [2] > 0 }

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Ak.upper()

Bv

Ck

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'item' instead of 'k' and 'v' in the loop.

Using the key instead of value in the condition.

Not converting keys to uppercase.

The comprehension uses k.upper() as key, v as value, and iterates over k, v in data.items(). The condition filters values greater than 0.