Interpolation for missing numerics in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to fill missing values in the 'score' column using linear interpolation.

Data Analysis Python

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

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

Adropna

Binterpolate

Cfillna

Dreplace

Attempts:

3 left

💡 Hint

Common Mistakes

Using fillna() without specifying a value does not estimate missing values.

dropna() removes rows instead of filling missing values.

The interpolate() method fills missing numeric values by estimating intermediate values linearly.

2fill in blank

medium

Complete the code to interpolate missing values in the 'temperature' column using the 'time' method.

Data Analysis Python

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

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A'time'

B'linear'

C'nearest'

D'index'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'linear' method when the index is a time series.

Using 'nearest' which picks closest values instead of interpolating.

The 'time' method uses the index as time values to interpolate missing data points.

3fill in blank

hard

Fix the error in the code to interpolate missing values forward in the 'humidity' column.

Data Analysis Python

df['humidity'] = df['humidity'].interpolate(method=[1], limit_direction='forward')

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A'backfill'

B'pad'

C'ffill'

D'nearest'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'pad' which is an alias but not accepted by interpolate() method.

Using 'backfill' which fills backward, opposite of forward.

The 'ffill' method propagates last valid observation forward to fill gaps.

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

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

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Alen(word)

Blen(word) > 3

Cword

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'word' instead of 'len(word)' for values.

Using 'word > 3' which compares string to number causing error.

The dictionary comprehension assigns each word's length as value and filters words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase keys to values only if value is positive.

Data Analysis Python

result = [1]: [2] for [3] 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' or 'v' causing errors.

Not converting keys to uppercase.

The comprehension uses uppercase keys, values from the dictionary, and iterates over key-value pairs.