We analyzed about 47 hours of Voyager 1 ultraviolet spectrometer observations of the Io plasma torus in order to determine the distributions of ion and electron density and electron temperature as five-dimensional functions of (1) radius (L), (2) System III longitude (&lgr;III), (3) System IV longitude (&lgr;IV), (4) Jovian local solar time (ϕ⊙), and (5) azimuth relative to Io (ϕIo). We present averaged profiles of electron density (ne) and temperature (Te) as one-dimensional functions of each of these five variables in turn. Each of these profiles is an average of the full five-dimensional distribution over the other four variables. Our Te(L) estimate is substantially the same as that determined from in situ observations by the Voyager 1 plasma science investigation. As for the azimuthal profiles, we find that the ne(&lgr;III) profile has a peak near &lgr;III=180¿, as expected from ground-based observations, while the Te(&lgr;III) profile peaks around &lgr;III=300¿. The Jovian surface magnetic field reaches its lowest magnitude on the Io footprints near the Te(&lgr;III) maximum, suggesting that part of the torus electron heating might be associated with Birkeland currents or some other magnetosphere-ionosphere coupling. In the Io frame, we find an apparent ne(ϕIo) maximum about 90¿ downstream from Io while the highest Te(ϕIo) occurs near Io, suggesting that electrons are locally heated by the Io atmosphere-torus MHD interaction. These two Te profiles suggest that field-aligned currents might comprise the long-sought additional (i.e., besides fresh ion pickup) electron-heating power source for torus emissions needed to resolve the torus energy crisis. In local solar time, we find that the Te(ϕ⊙) and ne(ϕ⊙) profiles peak between dusk and local midnight, with the former maximum nearer dusk and the latter nearer midnight. This combination suggests that the variation is due to an offset of the torus toward local midmorning, and perhaps that the cooling time is short. We also describe a general method for constraining solutions to be nonnegative when fitting data using the singular value decomposition least squares technique.