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How to perform an exploratory data analysis and ML algorithms on the NASA rocket launch dataset.

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Rocket-Launch

Introduction

Plans for a rocket launch occur over the course of years. So, NASA might have to choose a time and date several years before launch. If you've ever seen your local weather person or meteorologist, you know that sometimes it's hard to accurately predict weather even hours in advance.

Because large amounts of data are now available, weather predictions are more accurate than in the past, even taking into account the changing climate. But the stakes during a rocket launch are very high. It's not just that the astronauts might get cold because they didn't know they should bring a jacket. If NASA schedules the launch on the wrong day, it can be life-threatening.

While historical and prediction data are critical, there are also a number of factors that need to be analyzed on the day of a launch.

NASA collects data from a wide array of sources, including:

  • High-atmospheric Scientific Balloons
  • NOAA Weather
  • Satellite imagery
  • Remote sensors
  • Weather pattern experts

Determine the rocket launch questions to ask

Data science is an iterative process between the knowledge and understanding of what is today, the data that has been collected, and the questions that are being asked. New questions yield more information and the intention to gather more data.

When a new mission is being planned, NASA scientists have to ask: "What day in X years will be the least likely day to cause a launch push due to weather?" In the days leading up to the rocket launch, NASA scientists are the most critical in asking: "Will the weather in this area at this time cause any potential issues for the launch?"

To answer these questions, NASA has rocket, weather, and flight experts who create guidelines and models that help make a determination. They also have data from their own sensors and weather balloons, as well as trusted sources such as National Oceanic and Atmospheric Administration (NOAA) .

In this analysis, we don't have all of the data or expertise that NASA has on the day of a launch, but we do have simple weather data that's publicly available. They are:

  • Conditions (cloudy, partly cloudy, fair, rain, thunder, heavy storm)
  • Temperature
  • Humidity
  • Wind speed
  • Wind direction
  • Precipitation
  • Visibility
  • Sea level
  • Pressure

The Jupyter notebook goes through the Rocket launch dataset via an exploratory data analysis (EDA) with Python and finishes with making a final submission csv which was our ultimate aim.

You can download the data from this repo or directly from Microsoft Learn - https://docs.microsoft.com/en-us/learn/modules/collect-manipulate-data-python-nasa/3-explore-data.

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How to perform an exploratory data analysis and ML algorithms on the NASA rocket launch dataset.

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