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Stars-from-Gaia-DR2-and-RAVE-DR5

Stars-from-Gaia-DR2-and-RAVE-DR5

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context The RAVE dataset along with Gaia DR1 was used by Zackrisson et al. (2018), a paper on Dysonian SETI. Gaia is a mission of the European Space Agency (ESA) that aims to accurately measure the position, distance and magnitude of over a billion stars. RAVE is a radial velocity dataset. RAVE also provides spectrophotometric parallax data, as well as cross-identification of stars with a number of other datasets, including Gaia DR2. Content This dataset is a combination of RAVE DR5 and Gaia DR2 sources. The data is obtained using the query tool of the RAVE project. The SQL query follows: SELECT G.source_id,G.parallax,G.parallax_error,G.ra,G.dec,G.phot_g_mean_mag,G.phot_bp_mean_mag,G.phot_rp_mean_mag,G.l,G.b,G.pmra,G.pmdec, R.HRV AS r_hrv,R.Met_K AS r_metallicity,R.Algo_Conv_K AS r_quality,R.Mg AS r_mg,R.Si AS r_si,R.Ti AS r_ti,R.Fe AS r_fe,R.Ni AS r_ni,R.distance r_distance,R.parallax r_parallax,R.Jmag_2MASS r_jmag_2mass,R.Hmag_2MASS r_hmag_2mass,R.Kmag_2MASS r_kmag_2mass, R.RAdeg r_ra,R.DEdeg r_de, W1mag_ALLWISE r_w1mag_allwise, W2mag_ALLWISE r_w2mag_allwise, W3mag_ALLWISE r_w3mag_allwise, W4mag_ALLWISE r_w4mag_allwise, BTmag_TYCHO2 r_btmag_tycho2, VTmag_TYCHO2 r_vtmag_tycho2, Bmag_APASSDR9 r_bmag_apassdr9, Vmag_APASSDR9 r_vmag_apassdr9, rpmag_APASSDR9 r_rpmag_apassdr9, ipmag_APASSDR9 r_ipmag_apassdr9, Imag_DENIS r_imag_denis, Jmag_DENIS r_jmag_denis, Kmag_DENIS r_kmag_denis, B1mag_USNOB1 r_b1mag_usnob1, R1mag_USNOB1 r_r1mag_usnob1, B2mag_USNOB1 r_b2mag_usnob1, R2mag_USNOB1 r_r2mag_usnob1, Imag_USNOB1 r_imag_usnob1 FROM RAVEPUB_DR5.RAVE_DR2gaia_source G INNER JOIN RAVEPUB_DR5.RAVE_DR5 R ON R.RAVE_OBS_ID=G.RAVE_OBS_ID WHERE G.parallax IS NOT NULL The following processing was done: Removed rows with missing values in any of the following columns: "ra", "dec", "pmra", "pmdec", "l", "b", "parallax", "parallaxerror", "photgmeanmag", "photbpmeanmag", "photrpmeanmag", "rhrv", "rmetallicity", "rdistance", "rparallax", "rjmag2mass", "rhmag2mass", "rkmag2mass", "rmg", "rsi", "rfe", "rquality", "rra", "rde", "rw1magallwise", "rw2magallwise", "rw3magallwise", "rw4magallwise", "rbmagapassdr9", "rvmagapassdr9", "rrpmagapassdr9", "ripmagapassdr9", "rimagdenis", "rjmagdenis", "rkmagdenis" Averaged those values for rows that have the same Gaia "source_id". Note An alternative dataset is recommended: 257k Gaia DR2 stars. It contains sources from the Northern and Southern Hemispheres. Acknowledgements This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. References Kunder et al. (2016). The Radial Velocity Experiment (RAVE): Fifth Data Release. arXiv:1609.03210 Zackrisson et al. (2018). SETI with Gaia: The observational signatures of nearly complete Dyson spheres. arXiv:1804.08351

35 features

source_id (ignore)numeric252927 unique values
0 missing
ranumeric253040 unique values
0 missing
decnumeric253040 unique values
0 missing
pmranumeric253040 unique values
0 missing
pmdecnumeric253040 unique values
0 missing
lnumeric253040 unique values
0 missing
bnumeric253040 unique values
0 missing
parallaxnumeric253040 unique values
0 missing
parallax_errornumeric253040 unique values
0 missing
phot_g_mean_magnumeric42560 unique values
0 missing
phot_bp_mean_magnumeric40809 unique values
0 missing
phot_rp_mean_magnumeric62578 unique values
0 missing
r_hrvnumeric125834 unique values
0 missing
r_metallicitynumeric2146 unique values
0 missing
r_distancenumeric218044 unique values
0 missing
r_parallaxnumeric225661 unique values
0 missing
r_jmag_2massnumeric5881 unique values
0 missing
r_hmag_2massnumeric6283 unique values
0 missing
r_kmag_2massnumeric6404 unique values
0 missing
r_mgnumeric1944 unique values
0 missing
r_sinumeric2059 unique values
0 missing
r_fenumeric2085 unique values
0 missing
r_qualitynumeric62 unique values
0 missing
r_ranumeric248783 unique values
0 missing
r_denumeric242375 unique values
0 missing
r_w1mag_allwisenumeric6497 unique values
0 missing
r_w2mag_allwisenumeric6476 unique values
0 missing
r_w3mag_allwisenumeric6542 unique values
0 missing
r_w4mag_allwisenumeric4775 unique values
0 missing
r_bmag_apassdr9numeric6758 unique values
0 missing
r_vmag_apassdr9numeric5867 unique values
0 missing
r_rpmag_apassdr9numeric5657 unique values
0 missing
r_ipmag_apassdr9numeric5643 unique values
0 missing
r_imag_denisnumeric734 unique values
0 missing
r_jmag_denisnumeric1045 unique values
0 missing
r_kmag_denisnumeric1200 unique values
0 missing

19 properties

253040
Number of instances (rows) of the dataset.
35
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
35
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.

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