The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq. We center our analysis on post-natal development of the mammary gland, from puberty to post-involution. The new integrated study corresponds to RNA sequences from 53,686 individual cells, which greatly outnumbers the three initial data sets. The large volume of information provides new insights, as a better resolution of the previously detected Procr⁺ stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development.