Recent changes in power system, e.g. large-scale penetration of renewable energy source, have led to change the behavior of the electricity demand and market price drastically; this behavior is also influenced by various factors such as weather and economic conditions. The factors that affect such demand and price are complex and the analysis of these factors enables stakeholders to construct an electricity business strategy. Therefore, a framework is needed to analyze and interpret the relationships among these demand, price, and factors. Construction of a graphical model is an attractive approach to describe the statistical relationships among these factors; the directed graphical model flexibly visualizes the direct/indirect factors affecting the demand and price. In this study, the authors applied a graphical modeling scheme using the sparse partially linear additive models for factor analysis of electricity demand and price. The scheme is applied to a real-world dataset and discussed from the viewpoint of interpretability.