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 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 count(PAYLOAD_MASS__KG_) as Total_Payload_Mass from SPACEXTBL

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


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

 sns.catplot(y=”LaunchSite”,x=”FlightNumber”,hue=”Class”, data=df, aspect = 1,kind=’cat’)

plt.ylabel(“Launch Site”,fontsize=15)

plt.xlabel(“Flight Number”,fontsize=15)

 sns.catplot(y=”LaunchSite”,x=”FlightNumber”,hue=”Class”, data=df, aspect = 1)

plt.ylabel(“Launch Site”,fontsize=15)

plt.xlabel(“Flight Number”,fontsize=15)

sns.catplot(y=”LaunchSite”,x=”FlightNumber”,hue=”Class”, data=df, aspect = 1,kind=’scatter’)

plt.ylabel(“Launch Site”,fontsize=15)

plt.xlabel(“Flight Number”,fontsize=15)

sns.catplot(y=”LaunchSite”,x=”FlightNumber”,hue=”Class”, col=”Class”, data=df, aspect = 1)

plt.ylabel(“Launch Site”,fontsize=15)

plt.xlabel(“Flight Number”,fontsize=15)

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

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