textPCAPlot() plots words according to 2-D plot from 2 PCA components.
textPCAPlot(
word_data,
min_freq_words_test = 1,
plot_n_word_extreme = 5,
plot_n_word_frequency = 5,
plot_n_words_middle = 5,
titles_color = "#61605e",
title_top = "Principal Component (PC) Plot",
x_axes_label = "PC1",
y_axes_label = "PC2",
scale_x_axes_lim = NULL,
scale_y_axes_lim = NULL,
word_font = NULL,
bivariate_color_codes = c("#398CF9", "#60A1F7", "#5dc688", "#e07f6a", "#EAEAEA",
"#40DD52", "#FF0000", "#EA7467", "#85DB8E"),
word_size_range = c(3, 8),
position_jitter_hight = 0,
position_jitter_width = 0.03,
point_size = 0.5,
arrow_transparency = 0.1,
points_without_words_size = 0.2,
points_without_words_alpha = 0.2,
legend_title = "PC",
legend_x_axes_label = "PC1",
legend_y_axes_label = "PC2",
legend_x_position = 0.02,
legend_y_position = 0.02,
legend_h_size = 0.2,
legend_w_size = 0.2,
legend_title_size = 7,
legend_number_size = 2,
seed = 1002
)A 1- or 2-dimensional word plot, as well as tibble with processed data used to plot..
Dataframe from textPCA
Select words to significance test that have occurred at least min_freq_words_test (default = 1).
Number of words that are extreme on Supervised Dimension Projection per dimension. (i.e., even if not significant; per dimensions, where duplicates are removed).
Number of words based on being most frequent. (i.e., even if not significant).
Number of words plotted that are in the middle in Supervised Dimension Projection score (i.e., even if not significant; per dimensions, where duplicates are removed).
Color for all the titles (default: "#61605e")
Title (default " ")
Label on the x-axes.
Label on the y-axes.
Manually set the length of the x-axes (default = NULL, which uses ggplot2::scale_x_continuous(limits = scale_x_axes_lim); change e.g., by trying c(-5, 5)).
Manually set the length of the y-axes (default = NULL; which uses ggplot2::scale_y_continuous(limits = scale_y_axes_lim); change e.g., by trying c(-5, 5)).
Font type (default: NULL).
The different colors of the words (default: c("#398CF9", "#60A1F7", "#5dc688", "#e07f6a", "#EAEAEA", "#40DD52", "#FF0000", "#EA7467", "#85DB8E")).
Vector with minimum and maximum font size (default: c(3, 8)).
Jitter height (default: .0).
Jitter width (default: .03).
Size of the points indicating the words' position (default: 0.5).
Transparency of the lines between each word and point (default: 0.1).
Size of the points not linked with a words (default is to not show it, i.e., 0).
Transparency of the points not linked with a words (default is to not show it, i.e., 0).
Title on the color legend (default: "(PCA)".
Label on the color legend (default: "(x)".
Label on the color legend (default: "(y)".
Position on the x coordinates of the color legend (default: 0.02).
Position on the y coordinates of the color legend (default: 0.05).
Height of the color legend (default 0.15).
Width of the color legend (default 0.15).
Font size (default: 7).
Font size of the values in the legend (default: 2).
Set different seed.
see textPCA
# The test-data included in the package is called: DP_projections_HILS_SWLS_100
# Supervised Dimension Projection Plot
principle_component_plot_projection <- textPCAPlot(PC_projections_satisfactionwords_40)
principle_component_plot_projection
names(DP_projections_HILS_SWLS_100)
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