Python for Data Science Online Programming test Answers 2022

Are you looking for the Answers to NPTEL Python for Data Science Online Programming test? This article will help you with the answer to the National Programme on Technology Enhanced Learning (NPTEL) Course “ NPTEL Python for Data Science Online Programming test

What is Python for Data Science?

While hard skills teach us what to do, soft skills tell us how to apply our hard skills in a social environment. The focus of the course is to develop a wide variety of soft skills starting from communication, to working in different environments, developing emotional sensitivity, learning creative and critical decision making, developing awareness of how to work with and negotiate with people and to resolve stress and conflict in ourselves and others.
The uniqueness of the course lies in how a wide range of relevant issues are raised, relevant skills discussed and tips for integration provided in order to make us effective in workplace and social environments.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of the average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF THE AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Below you can find the answers for Python for Data Science Online Programming test

Python for Data Science Online Programming test Answers:-

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

For Online programming test help We share answer with our members first Click M

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

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

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

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

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?

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

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

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

Q10.How many unemployed clients have subscribed to deposit?

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

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

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

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

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