Data Wrangling

Data Wrangling

University

10 Qs

quiz-placeholder

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Data Wrangling

Data Wrangling

Assessment

Quiz

Computers

University

Easy

Created by

Revathi Prakash

Used 1+ times

FREE Resource

10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Assume that you are working on a data science project and needs to analyze dataset. Do you think data wrangling important in your analysis? Why.

Yes. Data wrangling is primarily focused on data visualization.

Yes. Data wrangling is a step that can be skipped in analysis.

Yes. Data wrangling prepares and cleans data for analysis.

No. Data wrangling is only necessary for large datasets.

2.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

What are the common steps involved in data wrangling process. Choose the one in correct order.

data collection,

data cleaning,

data transformation, data enrichment, data validation

data collection,

Data Analysis

data cleaning,

data transformation

data collection,

data transformation, Data visualization

Data storage

Data Analysis

Data Visualization

3.

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Krish is working on a project that involves analyzing customer feedback data. Help him to understand the difference between data cleaning and data wrangling?

Data cleaning means correcting errors. Data wrangling means transforming data into a usable format.

Data cleaning is the same as data wrangling.

Data wrangling only involves data visualization.

Data cleaning is only about removing duplicates. Data Wrangling means Data analysis

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is data normalization?

Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity.

Data normalization is the process of deleting all data from a database.

Data normalization involves creating multiple copies of the same data for backup.

Data normalization is the method of encrypting data to enhance security.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How to handle missing data during the wrangling process?

Assume missing data is zero

Duplicate existing data to fill gaps

Ignore missing data completely

Remove, impute, or encode missing data.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the significance of data visualization in data wrangling?

Data visualization helps in identifying patterns and anomalies during data wrangling

Data visualization has no impact on decision-making.

Data visualization complicates the data wrangling process.

Data visualization is only useful for creating reports.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the importance of data enrichment in the data wrangling process?

Data enrichment is only necessary for small datasets.

Data enrichment adds additional relevant information to the dataset, improving the quality

Data enrichment is the process of visualizing data.

Data enrichment involves deleting unnecessary data.

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