Data Study on Meteorites

Posted on May 7, 2018
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.


Data shows meteors are small pieces of space debris that fall down on the Earth every day. The vast majority of meteors burn up high in the atmosphere, but those few that reach the ground intact are called meteorites.

For this project, I wanted to get a sense of where on the surface of the Earth these meteorites have been found most often. I created an R shiny app using the leaflet package for drawing maps. The dataset I used comes from, originally taken from NASA. This dataset contains name, location, date, and mass information for about 50,000 meteorites that have been found on the ground so far, including about 1000 that have been seen by a person while falling.


To visualize the location of the meteorites, I created a map plotting the positions of all the meteorites in the dataset. The map shows each meteorite as a small circle, with the circle's size proportional to the mass of the meteorite. Zooming in past a certain point shows individual pieces for those meteorites of which many different pieces were found. The map can be filtered by the type of meteorite, the year it was found, and whether it was seen while falling or just found on the ground. (A summary detailing the different classes of meteorites can be found here.)  Hovering the mouse over a circle shows some of the information on that meteorite.

Data Study on Meteorites


In addition, I added a histogram tab that shows the count of meteorites by the year they were found, colored by class.  The histogram can also be filtered by class, year, and fall status.  The third tab shows a scrollable table of the filtered data.

Data Insights

Some insights about the data that I gained during the course of this project:

  • The distribution of the meteorites that were seen falling largely mirrors a population density map.  This makes sense since if there are more people living in an area, it is more likely that someone will see a falling meteorite.
  • However, the distribution of the meteorites that were found on the ground is highest in desert areas.  Presumably, this is because it is much easier to spot a meteorite on the ground if there is no obscuring vegetation.
  • The most common types of meteorite are chondrites (which are made of stone).  Iron meteorites are less common but tend to have higher masses.


In all, this project offered me an insightful look into the distribution of meteorites all over the world.  In the future, the data might be used by meteorite hunters or researchers to show where they are more likely to find certain types of meteorites.

Shiny App Link

About Author

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI