textPCAPlot

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
)

Arguments

word_data: Dataframe from textPCA
min_freq_words_test: Select words to significance test that have occurred at least min_freq_words_test (default = 1).
plot_n_word_extreme: Number of words that are extreme on Supervised Dimension Projection per dimension. (i.e., even if not significant; per dimensions, where duplicates are removed).
plot_n_word_frequency: Number of words based on being most frequent. (i.e., even if not significant).
plot_n_words_middle: 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).
titles_color: Color for all the titles (default: "#61605e")
title_top: Title (default " ")
x_axes_label: Label on the x-axes.
y_axes_label: Label on the y-axes.
scale_x_axes_lim: 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)).
scale_y_axes_lim: 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)).
word_font: Font type (default: NULL).
bivariate_color_codes: The different colors of the words (default: c("#398CF9", "#60A1F7", "#5dc688", "#e07f6a", "#EAEAEA", "#40DD52", "#FF0000", "#EA7467", "#85DB8E")).
word_size_range: Vector with minimum and maximum font size (default: c(3, 8)).
position_jitter_hight: Jitter height (default: .0).
position_jitter_width: Jitter width (default: .03).
point_size: Size of the points indicating the words' position (default: 0.5).
arrow_transparency: Transparency of the lines between each word and point (default: 0.1).
points_without_words_size: Size of the points not linked with a words (default is to not show it, i.e., 0).
points_without_words_alpha: Transparency of the points not linked with a words (default is to not show it, i.e., 0).
legend_title: Title on the color legend (default: "(PCA)".
legend_x_axes_label: Label on the color legend (default: "(x)".
legend_y_axes_label: Label on the color legend (default: "(y)".
legend_x_position: Position on the x coordinates of the color legend (default: 0.02).
legend_y_position: Position on the y coordinates of the color legend (default: 0.05).
legend_h_size: Height of the color legend (default 0.15).
legend_w_size: Width of the color legend (default 0.15).
legend_title_size: Font size (default: 7).
legend_number_size: Font size of the values in the legend (default: 2).
seed: Set different seed.

Value

A 1- or 2-dimensional word plot, as well as tibble with processed data used to plot..

Examples

# 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
#> $final_plot

#> 
#> $description
#> [1] "INFORMATION ABOUT THE PROJECTION  INFORMATION ABOUT THE PLOT word_data = PC_projections_satisfactionwords_40 min_freq_words_test = 1 plot_n_word_extreme = 5 plot_n_word_frequency = 5 plot_n_words_middle = 5 bivariate_color_codes = #398CF9 #60A1F7 #5dc688 #e07f6a #EAEAEA #40DD52 #FF0000 #EA7467 #85DB8E word_size_range = 3 - 8 position_jitter_hight = 0 position_jitter_width = 0.03 point_size = 0.5 arrow_transparency = 0.5 points_without_words_size = 0.2 points_without_words_alpha = 0.2 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"
#> 
#> $processed_word_data
#> # A tibble: 292 × 13
#>    words           n Dim_PC1 Dim_PC2 check_extreme_max_PC1 check_extreme_max_PC2
#>    <chr>       <int>   <dbl>   <dbl>                 <dbl>                 <dbl>
#>  1 accepted        1  -11.4     4.79                     0                     0
#>  2 accomplish…     2  -10.3     7.52                     0                     0
#>  3 achievement     1    3.08   17.1                      0                     0
#>  4 active          1   -3.79    8.28                     0                     0
#>  5 adequate        1   -7.50    8.40                     0                     0
#>  6 alive           1    2.25   -1.43                     0                     0
#>  7 alone           1    8.31   -3.75                     0                     0
#>  8 ambitious       1   -8.43   -4.33                     0                     0
#>  9 amusement       1   11.8    -4.24                     0                     0
#> 10 analytical      1    2.28    6.42                     0                     0
#> # ℹ 282 more rows
#> # ℹ 7 more variables: check_extreme_min_PC1 <dbl>, check_extreme_min_PC2 <dbl>,
#> #   check_extreme_frequency <dbl>, check_middle_PC1 <dbl>,
#> #   check_middle_PC2 <dbl>, extremes_all <dbl>, colour_categories <chr>
#> 

names(DP_projections_HILS_SWLS_100)
#> [1] "word_data"

Arguments

Value

See also

Examples