Log transformation for skewed data in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the numpy library for log transformation.

Data Analysis Python

import [1] as np

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Anumpy

Bpandas

Cmatplotlib

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Importing pandas instead of numpy

Using matplotlib which is for plotting

Forgetting to import any library

We use numpy for numerical operations including log transformation.

2fill in blank

medium

Complete the code to apply log transformation to the 'Income' column in the DataFrame 'df'.

Data Analysis Python

df['log_income'] = np.[1](df['Income'])

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Aexp

Blog

Csqrt

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using square root instead of log

Using exponential function by mistake

Applying mean function which is not a transformation

The np.log function applies the natural logarithm to data, useful for reducing skewness.

3fill in blank

hard

Fix the error in the code to avoid log of zero or negative values by adding 1 before log transformation.

Data Analysis Python

df['log_sales'] = np.log(df['Sales'] [1] 1)

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A*

B-

C+

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Subtracting 1 which can cause negative values

Multiplying or dividing which changes scale incorrectly

Adding 1 before log avoids errors from zero or negative values.

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 len(word) [2] 3}

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Alen(word)

Bword.upper()

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.upper() instead of length

Using less than instead of greater than

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

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 k, v in data.items() if v [3] 0 }

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using original keys without uppercase

Using wrong comparison operator

Swapping keys and values

This comprehension creates a dictionary with uppercase keys and values where values are positive.