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Map-making is an important step for the data analysis of Cosmic MicrowaveBackground (CMB) experiments. It consists of converting the data, which aretypically a long, complex and noisy collection of measurements, into a map,which is an image of the observed sky. We present in this paper a newmap-making code named PICASSO (Polarization and Intensity CArtographer forScanned Sky Observations), which was implemented to construct intensity andpolarization maps from the Multi Frequency Instrument (MFI) of the QUIJOTE(Q-U-I Joint TEnerife) CMB polarization experiment. PICASSO is based on thedestriping algorithm, and is suited to address specific issues of ground-basedmicrowave observations, with a technique that allows the fit of a templatefunction in the time domain, during the map-making step. This paper describesthe PICASSO code, validating it with simulations and assessing its performance.For this purpose, we produced realistic simulations of the QUIJOTE-MFI surveyof the northern sky (approximately $\sim 20,000\,$deg$^2$), and analysed thereconstructed maps with PICASSO, using real and harmonic space statistics. Weshow that, for this sky area, PICASSO is able to reconstruct, with highfidelity, the injected signal, recovering all the scales with $\ell>10$ in TT,EE and BB. The signal error is better than 0.001% at $20<\ell<200$. Finally, wevalidated some of the methods that will be applied to the real wide-surveydata, like the detection of the CMB anisotropies via cross-correlationanalyses. Despite that the implementation of PICASSO is specific forQUIJOTE-MFI data, it could be adapted to other experiments.

The PICASSO map-making code: application to a simulation of the QUIJOTE northern sky survey