Now, we will turn to the file "ReticulumII.csv’, which contains a catalog of stars observed by Gaia in a small region around an “ultra-faint” dwarf galaxy orbiting the Milky Way named Reticulum II. This galaxy is drowned out by foreground stars from the Milky Way disk, which we can cleverly remove using the information from Gaia.
The .csv file given has a noticeable change that you will need to account for when loading it. Visually inspect the file to figure out what this change is, and then load the file in with pandas using the appropriate arguments needed to handle the changed format.
Make a plot of the “dec” column (y-axis) vs. the “ra” column (x-axis); also, fix the figure size to be square of dimensions 5 x 5 inches. RA (short for Right Ascension) and Dec (short for Declination) are what we call celestial coordinates, and they specify the position of a star, galaxy, or other astronomical object on the sky.
Remove some Milky Way foreground stars by a cut with on parallax: specifically, the new dataframe should contain only the rows with parallax < 0.75. Parallaxes are related to distances via distance (in pc) = 1/parallax, and so removing stars with large parallax with leave us with a sample of only the more distant stars. Store the output in a new dataframe called filtered_stars.
Now, make a plot of the same size but now using the “pmra” column (x-axis) vs the “pmdec” column. Here, the “pm” stands for Proper Motion, which is the apparent change in an astronomical object’s celestial coordinate position due to its motion in the tangential direction (i.e., not along the line of sight, but instead on the plane of the sky).
In your plot from (4), see whether you can identify a clump of stars with similar proper motions in both the x and y directions. (hint: look near (0,0), and feel free to change the axes limits!). Then, come up with a rectangular selection based on the pmra/pmdec columns that could be used to select for rows consistent with this signal (e.g.. pmra > -5).
Filter your parallax-filtered dataframe from (3), which was called filtered_stars, using the cuts you defined in (5). You can store the output in a dataframe with the same name, filtered_stars.
Now, plot the same plot from (3) except now using the filtered_stars dataframe. Do you see the dwarf galaxy now?