  We derive cosmological constraints from the probability distribution function
(PDF) of evolved large-scale matter density fluctuations. We do this by
splitting lines of sight by density based on their count of tracer galaxies,
and by measuring both gravitational shear around and counts-in-cells in
overdense and underdense lines of sight, in Dark Energy Survey (DES) First Year
and Sloan Digital Sky Survey (SDSS) data. Our analysis uses a perturbation
theory model (see companion paper Friedrich at al.) and is validated using
N-body simulation realizations and log-normal mocks. It allows us to constrain
cosmology, bias and stochasticity of galaxies w.r.t. matter density and, in
addition, the skewness of the matter density field.
  From a Bayesian model comparison, we find that the data weakly prefer a
connection of galaxies and matter that is stochastic beyond Poisson
fluctuations on <=20 arcmin angular smoothing scale. The two stochasticity
models we fit yield DES constraints on the matter density
$\Omega_m=0.26^{+0.04}_{-0.03}$ and $\Omega_m=0.28^{+0.05}_{-0.04}$ that are
consistent with each other. These values also agree with the DES analysis of
galaxy and shear two-point functions (3x2pt) that only uses second moments of
the PDF. Constraints on $\sigma_8$ are model dependent
($\sigma_8=0.97^{+0.07}_{-0.06}$ and $0.80^{+0.06}_{-0.07}$ for the two
stochasticity models), but consistent with each other and with the 3x2pt
results if stochasticity is at the low end of the posterior range.
  As an additional test of gravity, counts and lensing in cells allow to
compare the skewness $S_3$ of the matter density PDF to its LCDM prediction. We
find no evidence of excess skewness in any model or data set, with better than
25 per cent relative precision in the skewness estimate from DES alone.
