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MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yearSDSS-IV survey that will obtain resolved spectroscopy from 3600 $\AA$ to 10300$\AA$ for a representative sample of over 10,000 nearby galaxies. In thispaper, we derive spatially resolved stellar population properties and radialgradients by performing full spectral fitting of observed galaxy spectra fromP-MaNGA, a prototype of the MaNGA instrument. These data include spectra foreighteen galaxies, covering a large range of morphological type. We derive age,metallicity, dust and stellar mass maps, and their radial gradients, using highspectral-resolution stellar population models, and assess the impact of varyingthe stellar library input to the models. We introduce a method to determinedust extinction which is able to give smooth stellar mass maps even in cases ofhigh and spatially non-uniform dust attenuation.  With the spectral fitting we produce detailed maps of stellar populationproperties which allow us to identify galactic features among this diversesample such as spiral structure, smooth radial profiles with little azimuthalstructure in spheroidal galaxies, and spatially distinct galaxy sub-components.In agreement with the literature, we find the gradients for galaxies identifiedas early-type to be on average flat in age, and negative (- 0.15 dex / R$_e$ )in metallicity, whereas the gradients for late-type galaxies are on averagenegative in age (- 0.39 dex / R$_e$ ) and flat in metallicity. We demonstratehow different levels of data quality change the precision with which radialgradients can be measured. We show how this analysis, extended to the largenumbers of MaNGA galaxies, will have the potential to shed light on galaxystructure and evolution.

P-MaNGA: Full spectral fitting and stellar population maps from prototype observations