mlcourse.ai. Assignment #1 (demo)

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Exploratory data analysis with Pandas

1. How many men and women (sex feature) are represented in this dataset? *

1 point

21790 men and 10771 women

16346 men and 12532 women

21790 women and 10771 men

16346 women and 12532 men

2. What is the average age (age feature) of women? *

1 point

34.67

35.95

36.86

37.04

3. What is the percentage of German citizens (native-country feature)? *

1 point

1.13

0.42

1.42

0.36

4. What are the mean and standard deviation of age for those who earn more than 50K per year (salary feature)? *

1 point

45 +- 9.5 years

42 +- 11.5 years

41 +- 12.5 years

44 +- 10.5 years

5. What are the mean and standard deviation of age for those who earn less than 50K per year? *

1 point

37 +- 14 years

38 +- 14 years

39 +- 15 years

40 +- 15 years

6. Is it true that people who earn more than 50K have at least high school education? (education – Bachelors, Prof-school, Assoc-acdm, Assoc-voc, Masters or Doctorate feature) *

1 point

Yes

7. Find the maximum age of men of Amer-Indian-Eskimo race. *

1 point

8. Among whom is the proportion of those who earn a lot (>50K) greater: married or single men (marital-status feature)? Consider as married those who have a marital-status starting with Married (Married-civ-spouse, Married-spouse-absent or Married-AF-spouse), the rest are considered bachelors. *

1 point

Among married

Among single

9. What is the maximum number of hours a person works per week (hours-per-week feature)? How many people work such a number of hours, and what is the percentage of those who earn a lot (>50K) among them? *

1 point

102 hours/week, 20 people, 41% are rich

99 hours/week, 95 people, 30% are rich

99 hours/week, 85 people, 29% are rich

90 hours/week., 70 people, 34% are rich

10. Count the average time of work (hours-per-week) for those who earn a little and a lot (salary) for each country (native-country). What will these be for Japan? *

1 point

41 and 48

46 and 43

44 and 48

41 and 40

Do you have any remarks concerning the assignment? In case of obvious errors/typos please use GitHub issues and/or pull requests (https://github.com/Yorko/mlcourse.ai).

You can checkout bonus assignments on Patreon https://www.patreon.com/ods_mlcourse or you can make a one-time pledge on Ko-Fi ko-fi.com/mlcourse_ai

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