While the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures of cells. Here, we invoked inDrop, a droplet-based single-cell RNA-Seq method, to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two strains of mice. Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare ghrelin-expressing epsilon-cells, exocrine cell types, vascular cells, Schwann cells, quiescent and activated pancreatic stellate cells, and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles, and validated their existence with immuno-histochemistry stains. Moreover, among human beta-cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER-stress. Finally, we deconvolve bulk gene expression samples using single-cell RNA-Seq to detect disease associated differential expression. Thus, our cross-species dataset provides a resource for the discovery of novel cell type-specific and cell type-restricted transcription factors, signaling receptors, and medically-relevant genes.