Applied Data Science Capstone Coursera Quiz Answers

Applied Data Science Capstone Week 01 Quiz Answers

Check Points: Data Collection API Answers

Q1. Did you Request and parse the SpaceX launch data using the GET request?

• Yes
• No

Q2. Did you filter the dataframe to only include Falcon 9 launches?

• Yes
• No

Q3. Did you relace None values in the PayloadMass with the mean?

• Yes
• No

Graded Quiz: Data Collection API with Webscraping Answers

Q1. After you performed a GET request on the Space X API and convert the response to a dataframe using pd.json_normalize. What year is located in the first row in the column static_fire_date_utc?

• 2006

Q2. Using the API, how many Falcon 9 launches are thereafter we remove Falcon 1 launches?

• 90

Q3. At the end of the API data collection process, how many missing values are there for the column landing pad?

• 26

Q4. After making a request to the Falcon9 Launch Wiki page and creating a BeautifulSoup object what is the output of:

soup. title

• < td colspan=”9″ > First flight of Falcon 9 v1.0. < sup class=”reference” id=”cite_ref-sfn20100604_17-0″
• <table class=”wikitable plainrowheaders collapsible” style=”width: 100%;”>
• <title> List of Falcon 9 and Falcon Heavy launches – Wikipedia </title>

Check Points: Data Wrangling Answers

Q1. Did you calculate the number of launches on each site?

• Yes
• No

Q2. Did you calculate the number and occurrence of each orbit?

• Yes
• No

Q3. Did you calculate the number and occurrence of mission outcome per orbit type?

• Yes
• No

Q4. Did you create a landing outcome label from the outcome column?

• Yes
• No

Graded Quiz: Data Wrangling Quiz Answers

Q1. How many launches came from CCAFS SLC 40?

• 55

Q2. What was the success rate?

• 80%
• 67%
• 40%

Q3. In the lab you used the method .value_counts() to determine the number and occurrence of each orbit in the column Orbit. What was the value for Orbit with the column name GTO.

• 27

Q4. How many landing outcomes in the column landing_outcomes had a value of none.

• 19

Applied Data Science Capstone Week 02 Quiz Answers

Check Points: Exploratory Analysis Using SQL Answers

Q1. Have you created a Db2 database asset in your IBM Watson Studio project?

• Yes
• No

Q2. Have you loaded SpaceX dataset into Db2 Table?

• Yes
• No

Q3. Have you used SQL queries with the SQL magic commands in Python to perform EDA?

• Yes
• No

Exploratory Data Analysis using SQL Answers

Q1. Which of the following will retrieve the most recent date from the spacex table?

• SELECT MAXIMUM(Date) from SPACEXTBL
• SELECT HIGHEST(Date) from SPACEXTBL
• SELECT DATE FROM SPACEXTBL WHERE DATE=MAX(DATE)
• SELECT max(Date) from SPACEXTBL

Q2. Which of the following queries display the minimum payload mass?

• select payload_mass__kg_ from SPACEXTBL order by payload_mass__kg_ group by booster_version LIMIT 1
• select payload_mass__kg_ from SPACEXTBL order by payload_mass__kg_ desc LIMIT 1
• select min(payload_mass__kg_) from SPACEXTBL
• select payload_mass__kg_ from SPACEXTBL where payload_mass__kg_=(select max(payload_mass__kg_) from SPACEXTBL) LIMIT 1

Q3. You are writing a query that will give you the total payload_mass_kg carried by the booster versions. The mass should be stored in the mass column. You want the result column to be called “Total_Payload_Mass”. Which of the following SQL queries is correct?

• SELECT sum(PAYLOAD_MASS__KG_) as Total_Payload_Mass from SPACEXTBL
• SELECT sum(PAYLOAD_MASS__KG_) from SPACEXTBL
• SELECT count(PAYLOAD_MASS__KG_) as Total_Payload_Mass from SPACEXTBL

Q4. Which of the following query to display 5 records launched on Friday?

• SELECT * FROM SPACEXTBL where DAYNAME(DATE)=’Friday’ LIMIT 5
• SELECT * FROM SPACEXTBL where DAY(DATE)=’Friday’ LIMIT 5

Q5. What are the unique launch sites mentioned in the Spacex table?

• CCAS LC-40,KSC LC-39A
• CCAFS LC-40,KSC LC-39B
• CCAFS LC-40,KSC LC-39A
• None of the Above

Exploratory Data Analysis for Data Visualization Answers

Q1. What type of data does a Bar Chart best represent?

• Location Data
• Numerical
• Categorical
• None of the above

Q2. What are the total number of columns in the features dataframe after applying one hot encoding to columns Orbits, LaunchSite, LandingPad and Serial .

Here the features  dataframe consists of the following columns FlightNumber’, ‘PayloadMass’, ‘Orbit’, ‘LaunchSite’, ‘Flights’, ‘GridFins’, ‘Reused’, ‘Legs’, ‘LandingPad’, ‘Block’, ‘ReusedCount’, ‘Serial’

• 120
• 80
• 83
• 96

Q3. The catplot code to show the scatterplot of  FlightNumber vs LaunchSite with x as FlightNumber, and y to Launch Site and hue to ‘Class’ is

Applied Data Science Capstone Week 03 Quiz Answers

Q1. How can you add marking objects such as circles, markers, or lines on a Folium map? (Click all choices that apply)

• add_node(map, object)
• map.add_child(object)
• map.add_to(object)
• object.add_to(map)

Q2. If you want to add multiple markers with similar coordinates on the Folium map, which Folium plugin you should use?

• MarkerCluster
• MarkerGroup
• MarkerContainer
• Markers should be add to map directly without any extra layer

Q3. Which attribute is used to provide available selections (such as a list of launch sites) for a Plotly DropDown input?

• input
• values
• placeholder
• options

Q4. How can we associate the result of a callback function (like a Ploty figure) to an element defined in the application layout

• Using a unique component id
• Dash automatically render the result of a callback function
• Using component name

Q5. Can we add multiple input components to a dash callback function

• Yes
• No

Applied Data Science Capstone Week 04 Quiz Answers

Graded Quiz: Predictive Analysisis Answers

Q1. How many records were there in the test sample?

• 18

Q2. For Support Vector Machines, what kernel has the best result on the validation dataset

• linear
• rbf
• sigmoid

Q3. After selecting the best hyperparameters for the decision tree classifier using the validation data, what was the accuracy achieved on the test data

• 83.33%
• 73.33%
• 93.33%

All Quiz Answers of multiple Specializations or Professional Certificates programs:

Course 1: What is Data Science?

Course 2: Tools for Data Science

Course 3: Data Science Methodology

Course 4: Python for Data Science, AI & Development

Course 5: Python Project for Data Science

Course 6: Databases and SQL for Data Science with Python

Course 7: Data Analysis with Python