Check Your Knowledge About Cleansing a Dataset

Question 1

The following table shows the Rainfall (in mm) and the Average Temperature (in °C) for each city over the month of April.

City	Country	Rainfall (mm)	Average Temperature (°C)
Vancouver	Canada	100.8	9.8
Bogota	Colombia	90.1	15.2
Queenstown	New Zealand	67	11
Paris	France	25	32
Mombasa	Kenya	150	27

Taking a look at this, you notice that the average temperature for Paris, France, seems abnormally high! In previous years, the average temperature in April has been much lower. You are unsure whether or not the value is erroneous.

What are your options?

Delete the value and impute another value
Decide that the statistical treatment you are using is robust (i.e. not sensitive to outliers), and keep the value.
Decide that the statistical treatment is not robust, and delete the value.
All of the above

Question 2

Examine this block of code. What does it do?

import pandas as pd
STATUS_VALUES = ["GUEST","EMPLOYER","EMPLOYEE"]

df = pd.read_csv("mylittlecompany.csv")

def process(value):
    if value not in STATUS_VALUES:
        return "GUEST"
    else:
        return value

df["status"] = df["status"].map(process)

They assign the value “GUEST” to individuals that do not have the value “EMPLOYER” or “EMPLOYEE” for the “status” variable.
They assign the value “GUEST” only to individuals that have no value for the “status” variable.

Question 3
Which column in this table contains an error of irregularity?

identifier

age

first name

score

2873

27

Leila

39 points

1028

999

45 points

3892

78

Samir

89%

8273

12

Cindy

24 points
- Identifier
- Age
- First Name
- Score

Perform an Initial Data Analysis

Check Your Knowledge About Cleansing a Dataset

Evaluated skills

Question 1

Question 2

Question 3

identifier	age	first name	score
2873	27	Leila	39 points
1028	999		45 points
3892	78	Samir	89%
8273	12	Cindy	24 points