Data Cleaning

Question 1

Dataset must have these 5 characteristics

Answer 1

Validity
Accuracy
Completeness
Consistency
Uniformity

Question 2

Four common issues revolving Data Cleaning

Answer 2

Unnecessary Data
Missing Data
Irregular Data
Inconsistent Data

Question 3

Three types of Unnecessary Data

Answer 3

Uninformative/Repetitive
Irrelevant
Duplicates

Question 4

PII

Answer 4

Should be removed; any information that can identify an individual user

Question 5

3 ways to classify missing data

Answer 5

Missing Completely at Random
Missing at Random
Missing not at Random

Question 6

Missing Completely at Random

Answer 6

no relationship between missing data and data

Question 7

Missing at Random

Answer 7

missing data is related to the observed but not unobserved data

Question 8

Missing not at Random

Answer 8

Missing Data is related to the unobserved data, not the observed

Question 9

How can you handle missing data?

Answer 9

Drop feature
Impute the value
Flag the missing info

Question 10

Irregular Data

Answer 10

outliers - found with IQR rule
data contradicting business or domain knowledge. findings and data from reliable sources, or intuition

Question 11

Inconsistent Data

Answer 11

data not in consistent form or syntax,
Capitalization
Formats
Misspelled words