Python for Data Analysis: Step-By-Step with Projects - Missing Data Overview

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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is one of the main challenges with missing data in datasets?
It is always random.
It can lead to inaccurate analysis results.
It has no impact on machine learning models.
It is easy to identify.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which method in pandas helps to check the non-null count for each column?
info
notna
isna
describe
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does pandas interpret missing values by default when reading a CSV file?
As a negative number
As an empty string
As NaN
As zero
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the isna method in pandas return?
A count of missing values
A list of missing values
A dataframe with Boolean values indicating missing data
A summary of non-missing data
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which method can be used to summarize the number of missing data within each column?
value_counts
sum
describe
info
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is one strategy for handling missing data?
Ignoring it
Dropping rows or columns with missing values
Converting it to zero
Replacing it with random numbers
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
When imputing missing data, what is a common approach for numerical columns?
Using the mean or median
Using the mode
Using random values
Using a constant string
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