Python For Data Science Online Non Proctored Exam 16 September 2022

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IMPORTANT CERTIFICATION CRITERIA

Candidates have to come to the exam centre and take the theory test on Sep 16, 2022.  It is mandatory to take the Proctored in-person final exam to obtain a certificate.

To pass the course and get a certificate:

Assignment score >= 40/100 AND Non Proctored exam score >= 40/100 AND Proctored exam score >= 40/100
        OR
Assignment score >= 10/25 AND Non Proctored exam score >= 10/25 AND Proctored exam score >= 20/50

All 3 conditions have to be satisfied. All the best to the candidates!

Assignment NameAnswers
Python For Data Science Assignment 1Click Here
Python For Data Science Assignment 2Click Here
Python For Data Science Assignment 3Click Here
Python For Data Science Assignment 4Click Here

Python For Data Science Online Non Proctored Exam 16 September 2022 Second Session 8 PM to 11 PM

1. Which of these crops are produced during the Summer season? (select option with all that apply)

a. Arecanut, Arhar/Tur, Bajra, Castor seed
b. Paddy, Maize, Moong (Green Gram), Onion, Sunflower
c. Banana, Coriander, Gram, Rapeseed & Mustard
d. Rice, Sugarcane, Paddy, Tomato

Answer:- b

2. During which year did Haryana have the highest crop production?

a. 2013
b. 2011
c. 1997
d. 2008

Answer:- b

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Python For Data Science Online Non Proctored Exam 16 September 2022

3. The maximum and minimum area for production were in the years?

a. 1997 and 2014
b. 1998 and 2015
c. 1997 and 2015
d. 1999 and 2005

Answer:- c

4. Which state in India had the second lowest crop production? (overall, for all years)

a. Meghalaya
b. Chandigarh
c. Mizoram
d. Manipur

Answer:- c

5. What were the top three produced crops in the year 2012?

a. Wheat, Potato, Rice
b. Coconut, Potato, Sugarcane
c. Coconut, Sugarcane, Rice
d. Rice, Sugarcane, Maize

Answer:- c

6. What is the standard deviation for Area of production?

a. 52957.44 (approx.)
b. 12167.42 (approx.)
c. 49177.60 (approx.)
d. 48848.27 (approx.)

Answer:- d

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Python For Data Science Online Non Proctored Exam 16 September 2022

7. Which is the crop that gave the highest production to the state of Andhra Pradesh?

a. Sugarcane
b. Wheat
c. Banana
d. Coconut

Answer:- d

8. Which of the following statements is true? (Select all that applies)

Answer:- b, d

9. Which state has the lowest area of production?

Answer:- b

10. What is the mean for the area of production?

Answer:- c

11. What is the correlation coefficient between Area and Production?

Answer:- d

12. The crops that had the highest production (in the correct order) were?

Answer:- c

13. Which is the only crop that has the highest production during autumn, summer, and winter?

Answer:- a

14. The Root mean square value of the Linear regression model is

Answer:- a

15. The MAE of the Linear regression model is

Answer:- b

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Python For Data Science Online Non-Proctored Exam 16 September 2022 First Session 10 AM to 1 PM

Follow the instructions given below and answer the questions

i. Read the given dataset apy_1.csv

ii. Drop the rows with missing values if any

1. Which of the following statement(s) is/are TRUE?

a. The overall production during the Kharif season is 1,195,933,000 (approx.)
b. The overall production during the Summer season is 34,549,800 (approx.)
c. The overall production during the Autumn season is 19,690,400 (approx.)
d. None of the above

Answer:- a, c

2. Which of the following set of crop(s) is/are produced during the Whole year season? (select option with all that apply)

a. Sugarcane, Garlic, Mango, Arhar/Tur
b. Paddy, Maize, Moong (Green Gram), Onion, Apple
c. Banana, Coriander, Gram, Rapeseed & Mustard, Sweet lime
d. Cabbage, Bitter Gourd, Masoor, Cucumber

Answer:- a, d

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Python For Data Science Online Non Proctored Exam 16 September 2022

3. Which district in India has the lowest crop production?

a. Coimbatore
b. Thrissur
c. Kannur
d. Mumbai

Answer:- d

4. During which year did West Bengal have the highest crop production?

a. 2013
b. 2007
c. 1997
d. 2006

Answer:- b

5. Which state in India has the second highest crop production? (Overall, for all years)

a. Andhra Pradesh
b. Tamil Nadu
c. Kerala
d. Uttar Pradesh

Answer:- b

6. How are the variables Area and Production correlated?

a. There exists a positive correlation between Area and Production
b. There exists a negative correlation between Area and Production
c. Area and Production are not correlated
d. Cannot be determined

Answer:- a

7. What is the average crop production?

a. 17,065,810.29 (approx.)
b. 50,857.44 (approx.)
c. 242,361.35 (approx.)
d. 621,031.95 (approx.)

Answer:- d

8. What is the standard deviation of production?

a. 17,065,810.29 (approx.)
b. 50,857.44 (approx.)
c. 242,361.35 (approx.)
d. 621,031.95 (approx.)

Answer:- a

9. Due to some unknown reasons, the crop production for only two states was recorded for 2015. Which states are they?

a. Tamil Nadu and Kerala
b. Kerala and Andhra Pradesh
c. Odisha and Sikkim
d. Sikkim and Punjab

Answer:- c

10. The top three produced crops in the year 2005 are ______

a. Wheat, Potato, Rice
b. Coconut, Potato, Sugarcane
c. Coconut, Sugarcane, Rice
d. Sugarcane, Rice, Wheat

Answer:- c

11. State whether the given statements are True or False

I.Crop year and Area are weakly correlated
II.Crop year and Production are strongly correlated

a. I – True, II – False
b. I – False, II – True
c. I – False, II – False
d. I – True, II – True

Answer:- b

12. Which year has the lowest crop production?

a. 2011
b. 2010
c. 2015
d. 2009

Answer:- c

13. The crop that Maharashtra produced the most is ________

a. Sugarcane
b. Rice
c. Banana
d. Coconut

Answer:- a

14. What does the R-squared value calculated for the model built signify?

a. The model is good as the R-squared-value is close to 1
b. The model is not good as the R-squared-value is close to 0
c. R-squared-value does not show the performance of the mode
d. lR-squared-value cannot be computed with this data

Answer:- b

15. For the model that has been built using the information given above Q14, the RMSE of the linear regression model is ___________

a. 14708129.51738 (approx)
b. 18962432.76753 (approx)
c. 14718129.43235968 (approx)
d. 14708029.87934857 (approx)

Answer:- b

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Python For Data Science Online Non Proctored Exam 20 March 2022 Second Session 8.00 PM to 11.00 PM

Read the given datasets 'banking.csv'
Kindly use this attachment Bank Marketing Data Description

Q1. The total number of missing values in the dataframe are

a. 8 
b. 3
c. 0 
d. 50

Answer:- b. 3

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Python For Data Science Online Non Proctored Exam 16 September 2022

Q2. The total number of duplicated values in the dataframe are:

  • 8
  • 2
  • 5

Answer:- c. 2

Q3. What is the shape of the data after dropping the feature “Unnamed: 0”, missing values and duplicated values?

  • (5000,17) 
  • (5581,17) 
  • (5578,17) 
  • (4581,18)

Answer:- c. (5578,17) 

Q4. What is the average age of the clients those who have subscribed to deposit?

  • 33
  • 41
  • 18
  • 48

Answer:- b. 41

Q5. What is the maximum number of contacts performed during the campaign for the clients who have not subscribed to deposit?

  • 63
  • 32
  • 10
  • 21

Answer: b. 32

Q6. What is the count of unique education levels in the data and find out how many clients have completed secondary education?

  • 4 & 745 
  • 6 & 1871 
  • 4 & 2717 
  • 12 & 245

Answer: c. 4 & 2717 

Q7. What is the percentage split of the categories in the column “deposit”

  • Yes – 47% & No – 53% 
  • Yes – 40% & No – 60% 
  • Yes – 50% & No – 50% 
  • Yes – 30% & No – 70%

Answer:- a. Yes – 47% & No – 53% 

Q8. Generate a scatter plot of “age” and “balance” and choose which of the interpretation given below is correct?

  • Across all ages, most of the client’s average yearly balance is less than 20000 euros 
  • Across all ages, most of the client’s average yearly balance is greater than 20000 euros 
  • As the age increases the bank balance of client increase 
  • As the age decrease the bank balance of client decrease

Answer:- a. Across all ages, most of the client’s average yearly balance is less than 20000 euros 

Q9. How many clients with personal loan has housing loan as well? 

  • 321 
  • 397 
  • 2606 
  • 2254

Answer:- b. 397 

Q10. How many unemployed clients have not subscribed to deposit? 

  • 100 
  • 85 
  • 78 
  • 92

Answer:- c. 78

Q11. The command used to convert the categorical variables to indicator variables is: –

  •  pandas.get_indicator(data) 
  • pandas.get_dummies(data) 
  • pandas.reshape(data) 
  • pandas.reshape.module(data)

Answer:- b. pandas.get_dummies(data) 

Q12. The code below is used to get a list of unique column names excluding ‘deposit’ column. Fill in the blanks in the order of the blanks (1st blank, 2nd blank) with appropriate data types as given in the options

	features= ____ (____(data.columns)-set(['deposit']))
  • set and list 
  • set and set 
  • list and list 
  • list and set

Answer:- d. list and set

Q13. The command to predict the logistic regression model ‘model’ on test dataset (test) is: –

  • model.fit(test) 
  • model.prediction(test) 
  • model.LogisticRegression(test)
  • model.predict(test) 

Answer:- d. model.predict(test) 

Q14. What is the value of accuracy of the model on the test dataset? (Choose the appropriate range)

  • 20% to 60% 
  • 60% to 70% 
  • 71% to 85% 
  • 86% to 100%

Answer:- c. 71% to 85% 

Q15. What is the value of accuracy of the model on the test dataset? (Choose the appropriate range) 

  • 20% to 40% 
  • 41% to 60% 
  • 61% to 80% 
  • 81% to 100%

Answer:- c. 61% to 80% 

Python For Data Science Online Non Proctored Exam 20 March 2022 First Session 10.00 AM to 1.00 PM

Read the given datasets ‘bank_marketing.csv

Kindly use this attachment Bank Marketing Data Description

Q1. The total number of missing values in the dataframe are

a. 8 
b. 10 
c. 0 
d. 50

Answer:- c. 0 

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Python For Data Science Online Non Proctored Exam 16 September 2022

Q2. The total number of duplicated values in the dataframe are:

  • 50 
  • 15 
  • 21

Answer:- a. 0

Q3. What is the shape of the data after dropping the feature “Unnamed: 0”, missing values and duplicated values?

  • (5000,17) 
  • (5581,17) 
  • (5580,18) 
  • (4581,18)

Answer:- c. (5581,17) 

Q4. What is the average age of the clients those who have subscribed to deposit?

  • 39
  • 49
  • 32
  • 41

Answer:- d. 41

Q5. What is the maximum number of contacts performed during the campaign for the clients who have not subscribed to deposit?

  • 63
  • 32
  • 10
  • 5

Answer:- a. 63

Q6. What is the difference between the maximum balance (in euros) for the clients who have subscribed to deposit and for the clients who have not subscribed to the deposit?

  • 1747 
  • 1514 
  • 24373 
  • 75054

Answer:- c. 24373 

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Python For Data Science Online Non Proctored Exam 16 September 2022

Q7. What is the count of unique job levels in the data and find out how many clients are in the management level?

  • 10 & 1318 
  • 12 & 3134 
  • 13 & 2000 
  • 12 & 1318

Answer:- d. 12 & 1318

Q8. What is the percentage split of the categories in the column “deposit”?

  • Yes- 47% & No- 53% 
  • Yes – 40% & No- 60% 
  • Yes – 50% & No- 50% 
  • Yes – 30% & No- 70%

Answer:- a. Yes- 47% & No- 53% 

Q9. Generate a scatter plot of “age” vs “balance” and choose which of the following interpretation is correct?

  • Across all ages, most of client’s average yearly balance is greater than 20000 euros 
  • As the age increases the bank balance of client increase 
  • Across all ages, most of the client’s average yearly balance is less than 20000 euros 
  • As the age decreases the bank balance of client decrease

Answer:- c. Across all ages, most of the client’s average yearly balance is less than 20000 euros 

Q10. How many unemployed clients have subscribed to deposit?

  • 100 
  • 85 
  • 78 
  • 92

Answer:- d. 92

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Python For Data Science Online Non Proctored Exam 16 September 2022

Q11. The command used to convert the categorical variables to indicator variables is: –

  •  pandas.get_indicator(data) 
  • pandas.get_dummies(data) 
  • pandas.reshape(data) 
  • pandas.reshape.module(data)

Answer:- b. pandas.get_dummies(data) 

Q12. The code below is used to get a list of unique column names excluding ‘deposit’ column. Fill in the blanks in the order of the blanks (1st blank, 2nd blank) with appropriate data types as given in the options

	features= ____ (____(data.columns)-set(['deposit']))
  • set and list 
  • set and set 
  • list and list 
  • list and set

Answer:- d. list and set

Q13. The command to predict the logistic regression model ‘model’ on test dataset (test) is: –

  • model.fit(test) 
  • model.prediction(test) 
  • model.predict(test) 
  • model.LogisticRegression(test)

Answer:- c. model.predict(test) 

Q14. What is the value of accuracy of the model on the test dataset? (Choose the appropriate range)

  • 20% to 60% 
  • 61% to 70% 
  • 71% to 90% 
  • 91% to 100%

Answer:- c. 71% to 90% 

Q15. What is the value of accuracy of the model on the test dataset? (Choose the appropriate range) 

  • 20% to 40% 
  • 41% to 60% 
  • 61% to 80% 
  • 81% to 100%

Answer:- c. 61% to 80% 

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