Correlations between Habitable and Inhabitable Planets in our Solar System vs. Planets outside out Solar System
Data. This word seemingly comes up constantly in our society, but what is it? Data is the facts and statistics collected together for reference or analysis. We use data for so many things, such as the transformational analytics (aggregation, enrichment, and processing), learning analytics (regression, clustering, and classification), and predictive analytics (simulation and optimization). Data is a universal term and the process of collecting, analysis, and concluding a data set, to answer a/either qualitative or quantitative question(s) is used by everyone.
In Module 01, for my INFO 3204 class, Information Expositions, we took a dive into a data set of our choice, follow a checklist of questions, code the data, and analyze said data, in hopes of answering our central research question. For step one, I formulated the question of: “What are the noticeable patterns, trends, and/or relationships between the habitable terrestrial planets, and the inhabitable gaseous planets, with the potentially habitable planets in the Conservative and Optimistic habitable zones? In particular, the habitability of the planet’s Masses vs. the planet itself, the planet’s Distance to its star (“Sun” as shown on the graphs), the Star Type that the planet is orbiting, and the Star Type that the planet is orbiting vs. the Orbital Period of the planet.” In order to find data regarding our eight planets and the other, most up-to-date list of potential habitable planets, I used NASA’s Planetary Fact Sheet — Metric and NASA’s Planetary Fact Sheet — Ratio to Earth Values and Wikipedia’s List of Potentially Habitable Exoplanets in the Conservative and Optimistic Habitable Zones. I then proceeded to step two and three, in which I read in my CSV File data and checked the packaging, which it correctly answered to be (55,6), which accounts for the fifty-five columns and six rows. These two sources allowed me to create an Excel file for the four terrestrial planets, the four gaseous planets, and the forty-seven potentially habitable planets, which had the categories of “Name,” “Star,” “Star Type,” “Mass” (in Earth Masses), “Orbital Period” (in days), and “Distance from Sun” (in light-years).
Next I moved on to steps four, five, and six. For step four I had to check the top and the bottom of the data set to prove it had it all, which it did. Next, for step five I had to check the “n's” (aka the numbers), which was all planetary data based from my CSV File. For step six, I had to validate against an external data source, meaning I had to check the common purposes of the data set, which were that you could separate said data into the four habitable terrestrial planets, the four inhabitable gaseous planets, and the forty-seven other habitable planets. I then used step seven, which was to make plots, in order to answer my question and subset questions.
First, I took this information and set off to answer my first part of the subset of questions, which asked if the mass of the planet (in Earth Masses), and the planet itself (gaseous and inhabitable or terrestrial/other and habitable) had any noticeable patterns, trends, and/or relationships. I then graphed the planets names on the x-axis and the planet’s masses (in Earth Masses) on the y-axis, in order to see if there was a trend in the masses of the habitable terrestrial and other planets and the inhabitable gaseous planets.
At first glance, it appears that the mass of the planet does effect the habitability of that planet. In other words, if it has a bigger mass, then it is deemed as uninhabitable, but if it has a smaller mass, then it is habitable. This seems plausible, until you notice the two gaseous planets of Uranus and Neptune. In this visualization; however Uranus and Neptune are in fact as large, or if not smaller, than some of the other planets that are deemed as habitable. This small fact creates a rift in the data, showing that the mass of the planet does not come into play when the questioning if the planet is habitable or not. This was shocking to me, because I assumed that these massive planets would create a problem when it came to the habitability of the planet itself, but in reality, it doesn’t matter.
Next I answered by next subset question of, if the mass of the planet (in Earth Masses) had any noticeable patterns, trends, and/or relationships, to the planet’s distance from the star that it orbited and the potential habitability of the planets. In order to visually see if there was a correlation, I graphed the planets distance from it’s Star (“Sun” in this visualization) on the x-axis, and the planet’s mass (in Earth Masses) on the y-axis. Along with this, I identified the what planets appeared on each point by color, to make it easier to decipher which planet is which.
In graphing this information, I was shocked at the answer behind this subset question. This visualization shows that the planet’s distance from it’s star has absolutely no correlation on if it has a large or small mass, which as we know has no correlation to if it is habitable or not. Next, despite all of this, I made yet another mind-boggling discovery. I initially assumed that the planets distance from its star had everything to do with the planet’s habitability, since living things typically (from what we know about living things) need a light source, which acts as a source of warmth (i.e., Earth and our “Sun”). However, this is not true. The distance of the planet from its star has no correlation to the habitability of the planet.
Next, I dove deeper into my next subset question of if the mass of the planet (in Earth Masses) had any noticeable patterns, trends, and/or relationships, to the star type that the planet orbited, and the potential habitability of the planets. I graphed the planets star type that it orbited on the x-axis, and the planet’s mass (in Earth Masses) on the y-axis. Along with this, I identified the what planets appeared on each point by color, to make it easier to decipher which planet is which.
After analyzing this visualization, I noticed a trend that proved itself throughout the data that is represented in this graph. The trend is that G#V star types typically have massive planets orbiting them. I then noticed that the K#V star types have the next somewhat medium-sized planets (based off of their mass) orbiting them. Lastly, the M#V star types have the smallest sized planets orbiting them (based off of their mass). Next I dove into what the numbers included in the star types could mean, such as G2V, or M7V, in which I was able to notice that the numbers had no correlation to the sizes of the planets orbiting them. Also, it is good to realize the discrepancy behind the numbers and the correlations it has, because, as one could notice, that some of the star types have “UNK/UNK#” between the first and last letters. This is unknown data regarding the number that the star type is deemed. This data block could effect the results of this trend if it were to ever be updated correctly. Next, when looking at star types and the planet’s habitability, it is scientifically proven that our G2V star (our “Sun”) type is responsible for life on Earth. Unfortunately, based off of the graph above, we cannot infer that this star type, in particular, vs. the other star types are at all responsible for life on their orbiting planets or not.
Next, I answered my last subset question of if the star type that the planet was orbiting had any noticeable patterns, trends, and/or relationships, to the orbital period of the planet, and the potential habitability of the planets. I graphed the planets star type that it orbited on the x-axis, and the planet’s orbital period (in days) on the y-axis. Along with this, I identified the what planets appeared on each point by color, to make it easier to decipher which planet is which.
Similarly, I noticed a trend that can be seen on the visualization provided above. The trend that I found was that the G#V star types had planets with higher orbital periods orbiting them, while K#V and M#V star types had planets orbiting them with small orbital periods. This is an interesting trend, however, yet again, shows no correlation to the habitability of the planet at hand.
In conclusion, to answer my initial research question of: “What are the noticeable patterns, trends, and/or relationships between the habitable terrestrial planets, and the inhabitable gaseous planets, with the potentially habitable planets in the Conservative and Optimistic habitable zones? In particular, the habitability of the planet’s Masses vs. the planet itself, the planet’s Distance to its star (“Sun” as shown on the graphs), the Star Type that the planet is orbiting, and the Star Type that the planet is orbiting vs. the Orbital Period of the planet,” I had to analyze the results from each subset question and its visualization. In doing so, I have concluded that, based off of the variables of mass, star it orbits, star types it orbits, distance to its star, and the planets orbital period, there are no noticeable patterns, trends, and/or relationships between the habitable and inhabitable planets in our solar system and the habitability of the other planets in different solar systems. I believe that there would be a lot more correlations if I were to use data on the chemical properties, composition, and reactions that occur in the atmosphere and on the surface of each planet, rather than just the mass, distances, and star type that it orbits. I think that diving deeper would dig up many patterns, trends, and/or relationships between all of the planets at question.
Sources:
(https://nssdc.gsfc.nasa.gov/planetary/factsheet/) (https://en.wikipedia.org/wiki/List_of_potentially_habitable_exoplanets)
