This catalog consists of 2 files the first file with the 1000 brightest stars in the GAIA DR3 catalog and the second file with the 1000 closest stars (curtesy of Mark Popinchalk). There are 75 columns in these files. Most of these are the stars brightness in magnitudes in a certain wavelength bands. Bands are filters that only allow in certain frequencies of light, so the brightness can be measured at different wavelengths. Almost every entry also has a measured error. These all start with an e_ followed by the property. Also some properties give a 50, 84 and 16 value. This is the median, 16% and 84% values of that property based on the calculations. The data columns are:
GaiaEDR3 is an ID for the star.
RAdeg and DEdeg are the position of the star on the sky.
Plx is the stars parallax, while pmRA and pmDE are the stars proper motion or transverse velocity.
Gmag, BPmag and RPmag are the magnitudes in GAIA bands.
RV is the stars radial velocity.
WDprop is the probability the star is a white dwarf.
xcoord, ycoord and zcoord are the stars likely 3D position.
Uvel, Vvel and Wvel are the stars 3D velocities.
The rest are mostly magnitudes from other telescopes and may not exist for all stars. The brightnesses are all in apparent magnitudes (m), to convert to a distance independent absolute magnitudes (M) one can use the formula
M = m – 5 log10(d) + 5
The following code can be used to read the 2 files and convert them to pandas DataFrames.
import pandas as pd
from astropy.table import Table
table_b = Table.read('edr3_nearby_brightest.fits')
table_c = Table.read('edr3_nearby_closest.fits')
df_b = table_b.to_pandas()
df_c = table_c.to_pandas()
df_c['type'] = 'close'
df_b['type'] = 'bright'
df = pd.concat([df_b,df_c])
