Heatmap plots of themes from interviews with new teachers

These plots provide a very quick and rough look at clusters of new teachers and self-reported themes from interviews using the heatmap() function from {base} R and geom_tile() from {ggplot2}.

Heatmap in {base} R, Viridis colors, Scaled but Unordered

Heatmap in {base} R, Viridis colors, Scaled and Computationally-sorted

Heatmap in {base} R, Heat colors, Scaled and Computationally-sorted

Themes Heatmap in {ggplot2}, Viridis colors, Scaled by max value, but Unordered

Themes Heatmap in {ggplot2}, Viridis colors, Scaled by max value, and Computationally-sorted

This final plot uses principal component analysis (PCA) through the {seriation} package to sort and cluster the heatmap both by most-similar participants and related themes.

Themes Heatmap in {ggplot2}, Viridis colors, Scaled by percent presence, and Computationally-sorted

Modalities Heatmap in {ggplot2}, Viridis colors, Scaled but Unordered

Modalities Heatmap in {ggplot2}, Viridis colors, Scaled by max value, and Computationally-sorted

This final plot uses principal component analysis (PCA) through the {seriation} package to sort and cluster the heatmap both by modalities and themes.

Themes Heatmap in {ggplot2}, Viridis colors, Scaled by percent presence, and Computationally-sorted