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Section 3.5 Key Takeaways
Always visualize your data ! Summary statistics can hide patterns (and problems) in your data.
ggplot2 follows a consistent grammar: data + aesthetics + geometry.
geom_bar() counts rows automatically;
geom_col() plots pre-summarized values.
Use
labs(),
theme(), and
coord_flip() to improve clarity and readability.
facet_wrap() helps compare groups by creating small multiples.
Trend lines (
geom_smooth()), error bars (
geom_errorbar()), labels (
geom_text()), and reference lines (
geom_hline(),
geom_vline()) help communicate the story in your data.
