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Evaluation application for Space X launch sites

Jupyter Notebook 99.72% Python 0.28%
dash-plotly eda predictive-modeling webscraping cluster-analysis knn-classification random-forest

spacex-python-app's Introduction

# IBM_Data_Science_capstone
This Capstone Project is the final part of the IBM Data Science professional certificate.
The scenario is that of a Data Analyst tasked with analyzing the optimum location for a luanch site for a new space program.
The location analysis is based on historical data from SpaceX, and includes all the launch sites, booster versions, payloads, and success or failure of the launches. 
The SpaceX data is obtained from corporate data sets and webscraped from trustworthy websites.  After wrangling the data, preliminary data analysis with SQL was conducted and results visualized.  Subequently, launch locations are mapped using folium and plotly. Finally, a range of machine language tools are evaluated to establish the most appropriate for making predictions regarding the feasibility of target locations.  Finally, the results of the SpaceX's launches is captured in an interactive dashboard which allows the user to examine the performace of different boosters, payloads and locations.  

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