SpaceX Falcon 9 first stage Landing Prediction
Collecting the data: In this capstone, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because SpaceX can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against SpaceX for a rocket launch. In this lab, you will collect and make sure the data is in the correct format from an API. The following is an example of a successful and launch. Objectives In this lab, you will make a get request to the SpaceX API. You will also do some basic data wrangling and formating.
Request to the SpaceX API Clean the requested data
- jupyter-labs-spacex-data-collection-api.ipynb
Web scraping Falcon 9 and Falcon Heavy Launches Records from Wikipedia: In this lab, you will be performing web scraping to collect Falcon 9 historical launch records from a Wikipedia page titled List of Falcon 9 and Falcon Heavy launches
https://en.wikipedia.org/wiki/List_of_Falcon_9_and_Falcon_Heavy_launches Web scrap Falcon 9 launch records with BeautifulSoup:
Extract a Falcon 9 launch records HTML table from Wikipedia Parse the table and convert it into a Pandas data frame
- jupyter-labs-webscraping.ipynb
Using this Python notebook you will:
Understand the Spacex DataSet Load the dataset into the corresponding table in a Db2 database Execute SQL queries to answer assignment questions
Overview of the DataSet
SpaceX has gained worldwide attention for a series of historic milestones.
It is the only private company ever to return a spacecraft from low-earth orbit, which it first accomplished in December 2010. SpaceX advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars wheras other providers cost upward of 165 million dollars each, much of the savings is because Space X can reuse the first stage.
Therefore if we can determine if the first stage will land, we can determine the cost of a launch.
This information can be used if an alternate company wants to bid against SpaceX for a rocket launch.
This dataset includes a record for each payload carried during a SpaceX mission into outer space. 3. jupyter-labs-eda-sql-coursera_sqllite.ipynb
In this assignment, we will predict if the Falcon 9 first stage will land successfully. SpaceX advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is due to the fact that SpaceX can reuse the first stage. In this lab, you will perform Exploratory Data Analysis and Feature Engineering. Objectives Perform exploratory Data Analysis and Feature Engineering using Pandas and Matplotlib
Exploratory Data Analysis Preparing Data Feature Engineering
- jupyter-labs-eda-dataviz.ipynb.jupyterlite.ipynb
Interactive Visual Analytics with Folium lab
The launch success rate may depend on many factors such as payload mass, orbit type, and so on. It may also depend on the location and proximities of a launch site, i.e., the initial position of rocket trajectories. Finding an optimal location for building a launch site certainly involves many factors and hopefully we could discover some of the factors by analyzing the existing launch site locations.
In the previous exploratory data analysis labs, you have visualized the SpaceX launch dataset using matplotlib and seaborn and discovered some preliminary correlations between the launch site and success rates. In this lab, you will be performing more interactive visual analytics using Folium.
Objectives This lab contains the following tasks:
TASK 1: Mark all launch sites on a map TASK 2: Mark the success/failed launches for each site on the map TASK 3: Calculate the distances between a launch site to its proximities After completed the above tasks, you should be able to find some geographical patterns about launch sites.
- lab_jupyter_launch_site_location.jupyterlite.ipynb
Build an Interactive Dashboard with Ploty Dash
In this lab, you will be building a Plotly Dash application for users to perform interactive visual analytics on SpaceX launch data in real-time.
This dashboard application contains input components such as a dropdown list and a range slider to interact with a pie chart and a scatter point chart. You will be guided to build this dashboard application via the following tasks:
TASK 1: Add a Launch Site Drop-down Input Component TASK 2: Add a callback function to render success-pie-chart based on selected site dropdown TASK 3: Add a Range Slider to Select Payload TASK 4: Add a callback function to render the success-payload-scatter-chart scatter plot Note:Please take screenshots of the Dashboard and save them. Further upload your notebook to github.
The github url and the screenshots are later required in the presentation slides.
Space X advertises Falcon 9 rocket launches on its website with a cost of 62 million dollars; other providers cost upward of 165 million dollars each, much of the savings is because Space X can reuse the first stage. Therefore if we can determine if the first stage will land, we can determine the cost of a launch. This information can be used if an alternate company wants to bid against space X for a rocket launch. In this lab, you will create a machine learning pipeline to predict if the first stage will land given the data from the preceding labs.
- SpaceX_Machine_Learning_Prediction_Part_5.jupyterlite.ipynb
Objectives Perform exploratory Data Analysis and determine Training Labels
create a column for the class Standardize the data Split into training data and test data -Find best Hyperparameter for SVM, Classification Trees and Logistic Regression
Find the method performs best using test data