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Interpret the Axes of an Analysis

Source: R/interpret.R
interpret.Rd

One table to read the axes of a factorial analysis, whatever the analysis:

  • a multiple correspondence analysis: per axis, the active levels contributing more than the mean contribution, the positive side facing the negative one, and the spread between the two sides in percent of each question's contribution (Brigitte Le Roux and Henri Rouanet, Geometric data analysis, Kluwer, 2004; Brigitte Le Roux, Analyse geometrique des donnees multidimensionnelles, Dunod, 2014);

  • a correspondence analysis: the same for the row points and the column points, each margin against its own mean contribution, since each sums to 100 different number of points;

  • a principal component analysis: each active variable's mean and spread, then, per axis, its coordinate — which under `scale.unit` IS its correlation with the axis —, its contribution and its cos2.

The eigenvalues of the axes travel under the table, with Benzecri's modified rate for an MCA. `mca_interpret()` and `pca_interpret()` are the same tables, for one analysis each.

Usage

interpret(res, ...)

mca_interpret(
  res.mca,
  axes = 1:5,
  complete = FALSE,
  min_contrib = NULL,
  color = TRUE,
  eig = TRUE,
  n_axes = 8L,
  lang = NULL,
  type = NULL,
  spread = NULL
)

pca_interpret(
  res.pca,
  axes = 1:3,
  color = TRUE,
  eig = TRUE,
  n_axes = 8L,
  lang = NULL
)

Arguments

res

An analysis made with multiple_correspondence_analysis, correspondence_analysis or principal_component_analysis (or with FactoMineR::MCA(), CA() or PCA(), or GDAtools::speMCA() or csMCA()).

...

The arguments below. A correspondence analysis takes one more, `vars`: the two margins' names, as in `vars = c("CSER", "PR2017")`. By default, the names correspondence_analysis kept; after a bare FactoMineR::CA(), which keeps none, the table says “Rows” and “Columns”.

res.mca, res.pca

The analysis, for `mca_interpret()` and `pca_interpret()`.

axes

The axes to interpret, as an integer vector. By default, the first five of an MCA, two of a CA, three of a PCA.

complete

For an MCA or a CA, set to TRUE for the fuller summary: each side of the axis gains the point's coordinate and its cos2, and the table gains the spread between the two sides.

min_contrib

For an MCA or a CA, the contribution threshold, in percent. NULL (the default) is the mean contribution of the point's own set; 0 keeps every point.

color

Set to FALSE to build the table with no colour measure, and no data bar under the eigenvalues.

eig

The eigenvalues travel under the table. Set to FALSE in a document that already shows them, or that prints the summary several times to comment it column by column.

n_axes

How many axes the eigenvalue table prints. When some are left out, an ellipsis row states how many the cloud has.

lang

NULL (the session's language), "en" or "fr".

type

Deprecated. The output format is now options(tabxplor.print), or an explicit tab_md / tab_html call — see [ggfacto_summary].

spread

Deprecated. Folded into complete.

Value

A tabxplor table — see [ggfacto_summary] for how it prints.

See also

[ggfacto_summary], [benzecri_mrv()].

Examples

# \donttest{
# ONE option decides how every tabxplor table prints, an interpretation table included.
# In a script it goes once, at the top, beside the library() calls.
options(tabxplor.print = "html")

data(tea, package = "FactoMineR")
res.mca <- multiple_correspondence_analysis(tea, 1:18)
interpret(res.mca)
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl" rowspan="2"></th><th class="tx-l tx-bl tx-rv" rowspan="2">Question</th><th class="tx-r tx-num tx-br">contrib</th><th class="tx-l tx-br tx-bl" rowspan="2">Positive_levels</th><th class="tx-r tx-num tx-br"> </th><th class="tx-l tx-br tx-bl" rowspan="2">Negative_levels</th><th class="tx-r tx-num tx-br"> </th></tr><tr><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="13">Axe 1: 9.9% of variance (mod. 55%)</td><td class="tx-l tx-bl tx-rv">where</td><td class="tx-r tx-num tx-br g2">15.7%</td><td class="tx-l tx-br tx-bl">chain store+tea shop</td><td class="tx-r tx-num tx-br p3 tx-b">11.3%</td><td class="tx-l tx-br tx-bl">chain store</td><td class="tx-r tx-num tx-br m1 tx-b">4.4%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">tearoom</td><td class="tx-r tx-num tx-br g2">13.9%</td><td class="tx-l tx-br tx-bl">tearoom</td><td class="tx-r tx-num tx-br p3 tx-b">11.2%</td><td class="tx-l tx-br tx-bl">Not.tearoom</td><td class="tx-r tx-num tx-br m1 tx-b">2.7%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">11.2%</td><td class="tx-l tx-br tx-bl">tea bag+unpackaged</td><td class="tx-r tx-num tx-br p2 tx-b">6.8%</td><td class="tx-l tx-br tx-bl">tea bag</td><td class="tx-r tx-num tx-br m1 tx-b">4.3%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">friends</td><td class="tx-r tx-num tx-br g2">9.1%</td><td class="tx-l tx-br tx-bl">friends</td><td class="tx-r tx-num tx-br p1 tx-b">3.2%</td><td class="tx-l tx-br tx-bl">Not.friends</td><td class="tx-r tx-num tx-br m2 tx-b">6.0%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">resto</td><td class="tx-r tx-num tx-br g2">8.5%</td><td class="tx-l tx-br tx-bl">resto</td><td class="tx-r tx-num tx-br p2 tx-b">6.3%</td><td class="tx-l tx-br tx-bl">Not.resto</td><td class="tx-r tx-num tx-br m1 tx-b">2.2%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">8.1%</td><td class="tx-l tx-br tx-bl">p_variable</td><td class="tx-r tx-num tx-br p1 tx-b">3.5%</td><td class="tx-l tx-br tx-bl">p_branded</td><td class="tx-r tx-num tx-br m1 tx-b">3.0%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">tea.time</td><td class="tx-r tx-num tx-br g2">7.2%</td><td class="tx-l tx-br tx-bl">tea time</td><td class="tx-r tx-num tx-br p1 tx-b">3.1%</td><td class="tx-l tx-br tx-bl">Not.tea time</td><td class="tx-r tx-num tx-br m1 tx-b">4.1%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">pub</td><td class="tx-r tx-num tx-br g2">5.5%</td><td class="tx-l tx-br tx-bl">pub</td><td class="tx-r tx-num tx-br p1 tx-b">4.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">work</td><td class="tx-r tx-num tx-br g2">4.2%</td><td class="tx-l tx-br tx-bl">work</td><td class="tx-r tx-num tx-br p1 tx-b">3.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">How</td><td class="tx-r tx-num tx-br g2">3.9%</td><td class="tx-l tx-br tx-bl">other</td><td class="tx-r tx-num tx-br p1 tx-b">2.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">3.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">green</td><td class="tx-r tx-num tx-br m1 tx-b">3.0%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">lunch</td><td class="tx-r tx-num tx-br g2">2.8%</td><td class="tx-l tx-br tx-bl">lunch</td><td class="tx-r tx-num tx-br p1 tx-b">2.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">87.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">57.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">29.6%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="5">Axe 2: 8.1%<br>of variance<br>(mod. 28%)</td><td class="tx-l tx-bl tx-rv">where</td><td class="tx-r tx-num tx-br g2">28.6%</td><td class="tx-l tx-br tx-bl">tea shop</td><td class="tx-r tx-num tx-br p4 tx-b">23.9%</td><td class="tx-l tx-br tx-bl">chain store</td><td class="tx-r tx-num tx-br m2 tx-b">4.6%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">25.6%</td><td class="tx-l tx-br tx-bl">p_upscale</td><td class="tx-r tx-num tx-br p3 tx-b">20.5%</td><td class="tx-l tx-br tx-bl">p_branded</td><td class="tx-r tx-num tx-br m1 tx-b">2.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">23.4%</td><td class="tx-l tx-br tx-bl">unpackaged</td><td class="tx-r tx-num tx-br p3 tx-b">18.9%</td><td class="tx-l tx-br tx-bl">tea bag</td><td class="tx-r tx-num tx-br m2 tx-b">4.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">7.3%</td><td class="tx-l tx-br tx-bl">green</td><td class="tx-r tx-num tx-br p1 tx-b">3.3%</td><td class="tx-l tx-br tx-bl">Earl Grey</td><td class="tx-r tx-num tx-br m1 tx-b">2.4%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">80.5%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">66.6%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">13.9%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="10">Axe 3: 6.0% of variance (mod.<br>8%)</td><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">20.5%</td><td class="tx-l tx-br tx-bl">Earl Grey</td><td class="tx-r tx-num tx-br p2 tx-b">5.9%</td><td class="tx-l tx-br tx-bl">black</td><td class="tx-r tx-num tx-br m3 tx-b">14.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">breakfast</td><td class="tx-r tx-num tx-br g2">13.3%</td><td class="tx-l tx-br tx-bl">Not.breakfast</td><td class="tx-r tx-num tx-br p2 tx-b">6.4%</td><td class="tx-l tx-br tx-bl">breakfast</td><td class="tx-r tx-num tx-br m2 tx-b">6.9%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">sugar</td><td class="tx-r tx-num tx-br g2">13.0%</td><td class="tx-l tx-br tx-bl">sugar</td><td class="tx-r tx-num tx-br p2 tx-b">6.7%</td><td class="tx-l tx-br tx-bl">No.sugar</td><td class="tx-r tx-num tx-br m2 tx-b">6.3%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">How</td><td class="tx-r tx-num tx-br g2">12.1%</td><td class="tx-l tx-br tx-bl">lemon</td><td class="tx-r tx-num tx-br p1 tx-b">3.1%</td><td class="tx-l tx-br tx-bl">milk</td><td class="tx-r tx-num tx-br m2 tx-b">4.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">other</td><td class="tx-r tx-num tx-br m1 tx-b">3.7%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">home</td><td class="tx-r tx-num tx-br g2">8.3%</td><td class="tx-l tx-br tx-bl">Not.home</td><td class="tx-r tx-num tx-br p2 tx-b">8.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">evening</td><td class="tx-r tx-num tx-br g2">6.6%</td><td class="tx-l tx-br tx-bl">evening</td><td class="tx-r tx-num tx-br p1 tx-b">4.3%</td><td class="tx-l tx-br tx-bl">Not.evening</td><td class="tx-r tx-num tx-br m1 tx-b">2.3%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">friends</td><td class="tx-r tx-num tx-br g2">6.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">Not.friends</td><td class="tx-r tx-num tx-br m1 tx-b">4.2%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">always</td><td class="tx-r tx-num tx-br g2">6.3%</td><td class="tx-l tx-br tx-bl">always</td><td class="tx-r tx-num tx-br p1 tx-b">4.1%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">80.9%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">38.5%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">42.3%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="11">Axe 4: 5.2% of variance (mod.<br>3%)</td><td class="tx-l tx-bl tx-rv">How</td><td class="tx-r tx-num tx-br g2">21.6%</td><td class="tx-l tx-br tx-bl">milk</td><td class="tx-r tx-num tx-br p2 tx-b">6.6%</td><td class="tx-l tx-br tx-bl">other</td><td class="tx-r tx-num tx-br m3 tx-b">12.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">dinner</td><td class="tx-r tx-num tx-br g2">21.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">dinner</td><td class="tx-r tx-num tx-br m3 tx-b">19.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">13.1%</td><td class="tx-l tx-br tx-bl">unpackaged</td><td class="tx-r tx-num tx-br p2 tx-b">7.2%</td><td class="tx-l tx-br tx-bl">tea bag+unpackaged</td><td class="tx-r tx-num tx-br m2 tx-b">5.6%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">10.1%</td><td class="tx-l tx-br tx-bl">p_private label</td><td class="tx-r tx-num tx-br p1 tx-b">2.5%</td><td class="tx-l tx-br tx-bl">p_variable</td><td class="tx-r tx-num tx-br m1 tx-b">3.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">where</td><td class="tx-r tx-num tx-br g2">7.5%</td><td class="tx-l tx-br tx-bl">tea shop</td><td class="tx-r tx-num tx-br p1 tx-b">3.4%</td><td class="tx-l tx-br tx-bl">chain store+tea shop</td><td class="tx-r tx-num tx-br m1 tx-b">3.8%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">breakfast</td><td class="tx-r tx-num tx-br g2">5.9%</td><td class="tx-l tx-br tx-bl">breakfast</td><td class="tx-r tx-num tx-br p1 tx-b">3.1%</td><td class="tx-l tx-br tx-bl">Not.breakfast</td><td class="tx-r tx-num tx-br m1 tx-b">2.8%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">work</td><td class="tx-r tx-num tx-br g2">4.6%</td><td class="tx-l tx-br tx-bl">work</td><td class="tx-r tx-num tx-br p1 tx-b">3.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">tea.time</td><td class="tx-r tx-num tx-br g2">4.2%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">Not.tea time</td><td class="tx-r tx-num tx-br m1 tx-b">2.4%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">always</td><td class="tx-r tx-num tx-br g2">3.5%</td><td class="tx-l tx-br tx-bl">always</td><td class="tx-r tx-num tx-br p1 tx-b">2.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">lunch</td><td class="tx-r tx-num tx-br g2">3.5%</td><td class="tx-l tx-br tx-bl">lunch</td><td class="tx-r tx-num tx-br p1 tx-b">2.9%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">81.5%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">31.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">50.3%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-bb2" rowspan="8">Axe 5: 4.9% of<br>variance (mod. 2%)</td><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">24.0%</td><td class="tx-l tx-br tx-bl">p_unknown</td><td class="tx-r tx-num tx-br p3 tx-b">17.3%</td><td class="tx-l tx-br tx-bl">p_variable</td><td class="tx-r tx-num tx-br m2 tx-b">5.1%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">How</td><td class="tx-r tx-num tx-br g2">18.1%</td><td class="tx-l tx-br tx-bl">other</td><td class="tx-r tx-num tx-br p3 tx-b">14.2%</td><td class="tx-l tx-br tx-bl">alone</td><td class="tx-r tx-num tx-br m1 tx-b">2.4%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">lunch</td><td class="tx-r tx-num tx-br g2">13.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">lunch</td><td class="tx-r tx-num tx-br m3 tx-b">11.1%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">12.2%</td><td class="tx-l tx-br tx-bl">black</td><td class="tx-r tx-num tx-br p1 tx-b">4.2%</td><td class="tx-l tx-br tx-bl">green</td><td class="tx-r tx-num tx-br m2 tx-b">8.0%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">resto</td><td class="tx-r tx-num tx-br g2">10.8%</td><td class="tx-l tx-br tx-bl">resto</td><td class="tx-r tx-num tx-br p2 tx-b">7.9%</td><td class="tx-l tx-br tx-bl">Not.resto</td><td class="tx-r tx-num tx-br m1 tx-b">2.8%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">7.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">tea bag+unpackaged</td><td class="tx-r tx-num tx-br m2 tx-b">5.0%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">dinner</td><td class="tx-r tx-num tx-br g2">3.5%</td><td class="tx-l tx-br tx-bl">dinner</td><td class="tx-r tx-num tx-br p1 tx-b">3.2%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">81.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">46.9%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">34.5%</td></tr></tbody><tfoot><tr><td colspan="7"><div class="tx-foot">Contribution to the variance of the axis: a level on the positive side, contributing <span class="p1" style="font-weight:bold;">×1</span>; <span class="p2" style="font-weight:bold;">×2</span>; <span class="p3" style="font-weight:bold;">×5</span>; <span class="p4" style="font-weight:bold;">×10</span> the mean contribution; a level on the negative side, contributing <span class="m1" style="font-weight:bold;">×1</span>; <span class="m2" style="font-weight:bold;">×2</span>; <span class="m3" style="font-weight:bold;">×5</span>; <span class="m4" style="font-weight:bold;">×10</span> the mean contribution.<br><b>contrib</b>: the whole question's contribution to the axis</div></td></tr></tfoot></table></div>
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">Axe</th><th class="tx-r tx-num">eigenvalue</th><th class="tx-r tx-num">% variance</th><th class="tx-r tx-num tx-br">cumul.</th><th class="tx-r tx-num">Benzecri's<br>modified rate</th><th class="tx-r tx-num tx-br">cumul. mod.</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;var&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">Axe 1</td><td class="tx-r tx-num g2">0.148</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:100%">9.9%</td><td class="tx-r tx-num tx-br g2">9.9%</td><td class="tx-r tx-num g2">55.4%</td><td class="tx-r tx-num tx-br g2">55.4%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 2</td><td class="tx-r tx-num g2">0.122</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:82%">8.1%</td><td class="tx-r tx-num tx-br g2">18.0%</td><td class="tx-r tx-num g2">28.1%</td><td class="tx-r tx-num tx-br g2">83.4%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 3</td><td class="tx-r tx-num g2">0.090</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:60.7%">6.0%</td><td class="tx-r tx-num tx-br g2">24.0%</td><td class="tx-r tx-num g2">7.6%</td><td class="tx-r tx-num tx-br g2">91.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 4</td><td class="tx-r tx-num g2">0.078</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:52.6%">5.2%</td><td class="tx-r tx-num tx-br g2">29.2%</td><td class="tx-r tx-num g2">3.3%</td><td class="tx-r tx-num tx-br g2">94.3%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 5</td><td class="tx-r tx-num g2">0.074</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:49.7%">4.9%</td><td class="tx-r tx-num tx-br g2">34.1%</td><td class="tx-r tx-num g2">2.1%</td><td class="tx-r tx-num tx-br g2">96.5%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 6</td><td class="tx-r tx-num g2">0.071</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:48.1%">4.8%</td><td class="tx-r tx-num tx-br g2">38.9%</td><td class="tx-r tx-num g2">1.6%</td><td class="tx-r tx-num tx-br g2">98.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 7</td><td class="tx-r tx-num g2">0.068</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:45.7%">4.5%</td><td class="tx-r tx-num tx-br g2">43.4%</td><td class="tx-r tx-num g2">1.0%</td><td class="tx-r tx-num tx-br g2">99.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 8</td><td class="tx-r tx-num g2">0.065</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:44.1%">4.4%</td><td class="tx-r tx-num tx-br g2">47.7%</td><td class="tx-r tx-num g2">0.6%</td><td class="tx-r tx-num tx-br g2">99.7%</td></tr>
#> <tr class="tx-bt"><td class="tx-l tx-br tx-bl tx-rv">... of 27</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num tx-br">...</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num tx-br">...</td></tr>
#> <tr class="tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num g2">1.500</td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td></tr></tbody></table></div>
interpret(res.mca, axes = 1:2, complete = TRUE)
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl" rowspan="2"></th><th class="tx-l tx-bl tx-rv" rowspan="2">Question</th><th class="tx-r tx-num tx-br">contrib</th><th class="tx-l tx-br tx-bl" rowspan="2">Positive_levels</th><th class="tx-r tx-num">ctr</th><th class="tx-r tx-num">coord</th><th class="tx-r tx-num tx-br">cos2</th><th class="tx-l tx-br tx-bl" rowspan="2">Negative_levels</th><th class="tx-r tx-num">ctr </th><th class="tx-r tx-num">coord </th><th class="tx-r tx-num tx-br">cos2 </th><th class="tx-r tx-num tx-br">spread</th></tr><tr><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;row%&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;row%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="13">Axe 1: 9.9% of variance (mod. 55%)</td><td class="tx-l tx-bl tx-rv">where</td><td class="tx-r tx-num tx-br g2">15.7%</td><td class="tx-l tx-br tx-bl">chain store+tea shop</td><td class="tx-r tx-num p3 tx-b">11.3%</td><td class="tx-r tx-num g2">1.08</td><td class="tx-r tx-num tx-br g2">41%</td><td class="tx-l tx-br tx-bl">chain store</td><td class="tx-r tx-num m1 tx-b">4.4%</td><td class="tx-r tx-num g2">-0.43</td><td class="tx-r tx-num tx-br g2">32%</td><td class="tx-r tx-num tx-br g2">99.9%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">tearoom</td><td class="tx-r tx-num tx-br g2">13.9%</td><td class="tx-l tx-br tx-bl">tearoom</td><td class="tx-r tx-num p3 tx-b">11.2%</td><td class="tx-r tx-num g2">1.25</td><td class="tx-r tx-num tx-br g2">37%</td><td class="tx-l tx-br tx-bl">Not.tearoom</td><td class="tx-r tx-num m1 tx-b">2.7%</td><td class="tx-r tx-num g2">-0.30</td><td class="tx-r tx-num tx-br g2">37%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">11.2%</td><td class="tx-l tx-br tx-bl">tea bag+unpackaged</td><td class="tx-r tx-num p2 tx-b">6.8%</td><td class="tx-r tx-num g2">0.76</td><td class="tx-r tx-num tx-br g2">26%</td><td class="tx-l tx-br tx-bl">tea bag</td><td class="tx-r tx-num m1 tx-b">4.3%</td><td class="tx-r tx-num g2">-0.45</td><td class="tx-r tx-num tx-br g2">27%</td><td class="tx-r tx-num tx-br g2">99.1%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">friends</td><td class="tx-r tx-num tx-br g2">9.1%</td><td class="tx-l tx-br tx-bl">friends</td><td class="tx-r tx-num p1 tx-b">3.2%</td><td class="tx-r tx-num g2">0.36</td><td class="tx-r tx-num tx-br g2">24%</td><td class="tx-l tx-br tx-bl">Not.friends</td><td class="tx-r tx-num m2 tx-b">6.0%</td><td class="tx-r tx-num g2">-0.68</td><td class="tx-r tx-num tx-br g2">24%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">resto</td><td class="tx-r tx-num tx-br g2">8.5%</td><td class="tx-l tx-br tx-bl">resto</td><td class="tx-r tx-num p2 tx-b">6.3%</td><td class="tx-r tx-num g2">0.80</td><td class="tx-r tx-num tx-br g2">23%</td><td class="tx-l tx-br tx-bl">Not.resto</td><td class="tx-r tx-num m1 tx-b">2.2%</td><td class="tx-r tx-num g2">-0.28</td><td class="tx-r tx-num tx-br g2">23%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">8.1%</td><td class="tx-l tx-br tx-bl">p_variable</td><td class="tx-r tx-num p1 tx-b">3.5%</td><td class="tx-r tx-num g2">0.50</td><td class="tx-r tx-num tx-br g2">15%</td><td class="tx-l tx-br tx-bl">p_branded</td><td class="tx-r tx-num m1 tx-b">3.0%</td><td class="tx-r tx-num g2">-0.50</td><td class="tx-r tx-num tx-br g2">12%</td><td class="tx-r tx-num tx-br g2">79.3%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">tea.time</td><td class="tx-r tx-num tx-br g2">7.2%</td><td class="tx-l tx-br tx-bl">tea time</td><td class="tx-r tx-num p1 tx-b">3.1%</td><td class="tx-r tx-num g2">0.39</td><td class="tx-r tx-num tx-br g2">19%</td><td class="tx-l tx-br tx-bl">Not.tea time</td><td class="tx-r tx-num m1 tx-b">4.1%</td><td class="tx-r tx-num g2">-0.50</td><td class="tx-r tx-num tx-br g2">19%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">pub</td><td class="tx-r tx-num tx-br g2">5.5%</td><td class="tx-l tx-br tx-bl">pub</td><td class="tx-r tx-num p1 tx-b">4.4%</td><td class="tx-r tx-num g2">0.74</td><td class="tx-r tx-num tx-br g2">15%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num g1"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br g2"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">work</td><td class="tx-r tx-num tx-br g2">4.2%</td><td class="tx-l tx-br tx-bl">work</td><td class="tx-r tx-num p1 tx-b">3.0%</td><td class="tx-r tx-num g2">0.52</td><td class="tx-r tx-num tx-br g2">11%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num g1"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br g2"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">How</td><td class="tx-r tx-num tx-br g2">3.9%</td><td class="tx-l tx-br tx-bl">other</td><td class="tx-r tx-num p1 tx-b">2.3%</td><td class="tx-r tx-num g2">1.44</td><td class="tx-r tx-num tx-br g2">6%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num g1"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br g2"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">3.4%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num g1"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-l tx-br tx-bl">green</td><td class="tx-r tx-num m1 tx-b">3.0%</td><td class="tx-r tx-num g2">-0.85</td><td class="tx-r tx-num tx-br g2">9%</td><td class="tx-r tx-num tx-br g2"></td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">lunch</td><td class="tx-r tx-num tx-br g2">2.8%</td><td class="tx-l tx-br tx-bl">lunch</td><td class="tx-r tx-num p1 tx-b">2.4%</td><td class="tx-r tx-num g2">0.66</td><td class="tx-r tx-num tx-br g2">7%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num g1"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br g2"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">87.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-b">57.3%</td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-b">29.6%</td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br tx-b">74.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-bb2" rowspan="5">Axe 2: 8.1%<br>of variance<br>(mod. 28%)</td><td class="tx-l tx-bl tx-rv">where</td><td class="tx-r tx-num tx-br g2">28.6%</td><td class="tx-l tx-br tx-bl">tea shop</td><td class="tx-r tx-num p4 tx-b">23.9%</td><td class="tx-r tx-num g2">2.29</td><td class="tx-r tx-num tx-br g2">58%</td><td class="tx-l tx-br tx-bl">chain store</td><td class="tx-r tx-num m2 tx-b">4.6%</td><td class="tx-r tx-num g2">-0.40</td><td class="tx-r tx-num tx-br g2">28%</td><td class="tx-r tx-num tx-br g2">99.5%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">price</td><td class="tx-r tx-num tx-br g2">25.6%</td><td class="tx-l tx-br tx-bl">p_upscale</td><td class="tx-r tx-num p3 tx-b">20.5%</td><td class="tx-r tx-num g2">1.59</td><td class="tx-r tx-num tx-br g2">55%</td><td class="tx-l tx-br tx-bl">p_branded</td><td class="tx-r tx-num m1 tx-b">2.5%</td><td class="tx-r tx-num g2">-0.41</td><td class="tx-r tx-num tx-br g2">8%</td><td class="tx-r tx-num tx-br g2">81.4%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">how</td><td class="tx-r tx-num tx-br g2">23.4%</td><td class="tx-l tx-br tx-bl">unpackaged</td><td class="tx-r tx-num p3 tx-b">18.9%</td><td class="tx-r tx-num g2">1.86</td><td class="tx-r tx-num tx-br g2">47%</td><td class="tx-l tx-br tx-bl">tea bag</td><td class="tx-r tx-num m2 tx-b">4.5%</td><td class="tx-r tx-num g2">-0.42</td><td class="tx-r tx-num tx-br g2">23%</td><td class="tx-r tx-num tx-br g2">99.8%</td></tr>
#> <tr><td class="tx-l tx-bl tx-rv">Tea</td><td class="tx-r tx-num tx-br g2">7.3%</td><td class="tx-l tx-br tx-bl">green</td><td class="tx-r tx-num p1 tx-b">3.3%</td><td class="tx-r tx-num g2">0.81</td><td class="tx-r tx-num tx-br g2">8%</td><td class="tx-l tx-br tx-bl">Earl Grey</td><td class="tx-r tx-num m1 tx-b">2.4%</td><td class="tx-r tx-num g2">-0.29</td><td class="tx-r tx-num tx-br g2">15%</td><td class="tx-r tx-num tx-br g2">70.0%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-bl tx-rv">Above mean ctr</td><td class="tx-r tx-num tx-br tx-b">80.5%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-b">66.6%</td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-b">13.9%</td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-br tx-b">74.6%</td></tr></tbody><tfoot><tr><td colspan="12"><div class="tx-foot">Contribution to the variance of the axis: a level on the positive side, contributing <span class="p1" style="font-weight:bold;">×1</span>; <span class="p2" style="font-weight:bold;">×2</span>; <span class="p3" style="font-weight:bold;">×5</span>; <span class="p4" style="font-weight:bold;">×10</span> the mean contribution; a level on the negative side, contributing <span class="m1" style="font-weight:bold;">×1</span>; <span class="m2" style="font-weight:bold;">×2</span>; <span class="m3" style="font-weight:bold;">×5</span>; <span class="m4" style="font-weight:bold;">×10</span> the mean contribution.<br><b>contrib</b>: the whole question's contribution to the axis<br><b>coord</b>: coordinate on the axis<br>cos2: quality of representation<br><b>spread</b>: share of the group's contribution the gap between its two sides accounts for</div></td></tr></tfoot></table></div>
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">Axe</th><th class="tx-r tx-num">eigenvalue</th><th class="tx-r tx-num">% variance</th><th class="tx-r tx-num tx-br">cumul.</th><th class="tx-r tx-num">Benzecri's<br>modified rate</th><th class="tx-r tx-num tx-br">cumul. mod.</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;var&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">Axe 1</td><td class="tx-r tx-num g2">0.148</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:100%">9.9%</td><td class="tx-r tx-num tx-br g2">9.9%</td><td class="tx-r tx-num g2">55.4%</td><td class="tx-r tx-num tx-br g2">55.4%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 2</td><td class="tx-r tx-num g2">0.122</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:82%">8.1%</td><td class="tx-r tx-num tx-br g2">18.0%</td><td class="tx-r tx-num g2">28.1%</td><td class="tx-r tx-num tx-br g2">83.4%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 3</td><td class="tx-r tx-num g2">0.090</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:60.7%">6.0%</td><td class="tx-r tx-num tx-br g2">24.0%</td><td class="tx-r tx-num g2">7.6%</td><td class="tx-r tx-num tx-br g2">91.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 4</td><td class="tx-r tx-num g2">0.078</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:52.6%">5.2%</td><td class="tx-r tx-num tx-br g2">29.2%</td><td class="tx-r tx-num g2">3.3%</td><td class="tx-r tx-num tx-br g2">94.3%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 5</td><td class="tx-r tx-num g2">0.074</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:49.7%">4.9%</td><td class="tx-r tx-num tx-br g2">34.1%</td><td class="tx-r tx-num g2">2.1%</td><td class="tx-r tx-num tx-br g2">96.5%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 6</td><td class="tx-r tx-num g2">0.071</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:48.1%">4.8%</td><td class="tx-r tx-num tx-br g2">38.9%</td><td class="tx-r tx-num g2">1.6%</td><td class="tx-r tx-num tx-br g2">98.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 7</td><td class="tx-r tx-num g2">0.068</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:45.7%">4.5%</td><td class="tx-r tx-num tx-br g2">43.4%</td><td class="tx-r tx-num g2">1.0%</td><td class="tx-r tx-num tx-br g2">99.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 8</td><td class="tx-r tx-num g2">0.065</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:44.1%">4.4%</td><td class="tx-r tx-num tx-br g2">47.7%</td><td class="tx-r tx-num g2">0.6%</td><td class="tx-r tx-num tx-br g2">99.7%</td></tr>
#> <tr class="tx-bt"><td class="tx-l tx-br tx-bl tx-rv">... of 27</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num tx-br">...</td><td class="tx-r tx-num">...</td><td class="tx-r tx-num tx-br">...</td></tr>
#> <tr class="tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num g2">1.500</td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td></tr></tbody></table></div>

# a correspondence analysis draws the STRUCTURE of a crosstab's deviations and says nothing of
# their size, so the crosstab is asked for beside it, never instead of it:
crosstab <- tabxplor::tab(forcats::gss_cat, race, marital)
interpret(correspondence_analysis(crosstab))
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl" rowspan="2"></th><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">Variable</th><th class="tx-l tx-br tx-bl" rowspan="2">Positive_levels</th><th class="tx-r tx-num tx-br"> </th><th class="tx-l tx-br tx-bl" rowspan="2">Negative_levels</th><th class="tx-r tx-num tx-br"> </th></tr><tr><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;col%&gt;</th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-nb" rowspan="4">Axe 1:<br>88.8% of<br>variance</td><td class="tx-l tx-br tx-bl tx-rv">race</td><td class="tx-l tx-br tx-bl">Black</td><td class="tx-r tx-num tx-br p2 tx-b">72.6%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb"><td class="tx-l tx-br tx-bl tx-rv">race: above mean ctr</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">72.6%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b"></td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">marital</td><td class="tx-l tx-br tx-bl">Never married</td><td class="tx-r tx-num tx-br p2 tx-b">54.2%</td><td class="tx-l tx-br tx-bl">Married</td><td class="tx-r tx-num tx-br m1 tx-b">30.5%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">marital: above mean ctr</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">54.2%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">30.5%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-lbl tx-vname tx-b tx-bb2" rowspan="5">Axe 2: 11.2%<br>of variance</td><td class="tx-l tx-br tx-bl tx-rv">race</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td><td class="tx-l tx-br tx-bl">Other</td><td class="tx-r tx-num tx-br m2 tx-b">84.5%</td></tr>
#> <tr class="tx-b tx-bt tx-bb"><td class="tx-l tx-br tx-bl tx-rv">race: above mean ctr</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b"></td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">84.5%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">marital</td><td class="tx-l tx-br tx-bl">Widowed</td><td class="tx-r tx-num tx-br p2 tx-b">46.2%</td><td class="tx-l tx-br tx-bl">Married</td><td class="tx-r tx-num tx-br m1 tx-b">21.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv"></td><td class="tx-l tx-br tx-bl">Divorced</td><td class="tx-r tx-num tx-br p1 tx-b">26.0%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br g1"></td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">marital: above mean ctr</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">72.3%</td><td class="tx-l tx-br tx-bl"></td><td class="tx-r tx-num tx-br tx-b">21.1%</td></tr></tbody><tfoot><tr><td colspan="6"><div class="tx-foot">Contribution to the variance of the axis: a level on the positive side, contributing <span class="p1" style="font-weight:bold;">×1</span>; <span class="p2" style="font-weight:bold;">×2</span>; <span class="p3" style="font-weight:bold;">×5</span>; <span class="p4" style="font-weight:bold;">×10</span> the mean contribution; a level on the negative side, contributing <span class="m1" style="font-weight:bold;">×1</span>; <span class="m2" style="font-weight:bold;">×2</span>; <span class="m3" style="font-weight:bold;">×5</span>; <span class="m4" style="font-weight:bold;">×10</span> the mean contribution.</div></td></tr></tfoot></table></div>
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">Axe</th><th class="tx-r tx-num">eigenvalue</th><th class="tx-r tx-num">% variance</th><th class="tx-r tx-num tx-br">cumul.</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;var&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">Axe 1</td><td class="tx-r tx-num g2">0.041</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:100%">88.8%</td><td class="tx-r tx-num tx-br g2">88.8%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 2</td><td class="tx-r tx-num g2">0.005</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:12.6%">11.2%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num g2">0.046</td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td></tr></tbody></table></div>
tabxplor::tab(forcats::gss_cat, race, marital, pct = "row", color = "contrib", test = TRUE)
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-span" colspan="1"></th><th class="tx-span" colspan="6">marital</th><th class="tx-span" colspan="1"></th></tr><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">race</th><th class="tx-r tx-num">No answer</th><th class="tx-r tx-num">Never married</th><th class="tx-r tx-num">Separated</th><th class="tx-r tx-num">Divorced</th><th class="tx-r tx-num">Widowed</th><th class="tx-r tx-num">Married</th><th class="tx-r tx-num tx-br tx-bl tx-tot">Total</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;row%&gt;</th><th class="tx-r tx-num tx-unit"></th><th class="tx-r tx-num tx-unit"></th><th class="tx-r tx-num tx-unit"></th><th class="tx-r tx-num tx-unit"></th><th class="tx-r tx-num tx-unit"></th><th class="tx-r tx-num tx-br tx-bl tx-tot tx-unit">&lt;row% (n)&gt;</th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">Other</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ×1.29 ; OR: 1.00 ; ctr: 0% ; resid: +0.4 ; n: 2">0%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +7% ; ratio: ×1.28 ; OR: 1/1.01 ; ctr: 4% ; resid: +7.6 ; n: 633">32%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +2% ; ratio: ×1.62 ; OR: 1.26 ; ctr: 3% ; resid: +5.5 ; n: 110">6%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: -5% ; ratio: ÷1.46 ; OR: 1/1.88 ; ctr: 3% ; resid: -6.3 ; n: 212">11%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: -5% ; ratio: ÷2.35 ; OR: 1/3.04 ; ctr: 5% ; resid: -8.1 ; n: 70">4%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ×1.01 ; OR: 1/1.28 ; ctr: 0% ; resid: +0.4 ; n: 932">48%</td><td class="tx-r tx-num tx-br tx-bl tx-tot tx-b">100%<span class="tx-sec" style="font-weight:normal;"> ( 1 959)</span></td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Black</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ÷1.24 ; OR: 1.00 ; ctr: 0% ; resid: -0.3 ; n: 2">0%</td><td class="tx-r tx-num p3 tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +16% ; ratio: ×1.65 ; OR: 2.05 ; ctr: 34% ; resid: +23.0 ; n: 1 305">42%</td><td class="tx-r tx-num p1 tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +3% ; ratio: ×1.81 ; OR: 2.24 ; ctr: 7% ; resid: +9.3 ; n: 196">6%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ×1.00 ; OR: 1.24 ; ctr: 0% ; resid: +0.1 ; n: 495">16%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ×1.00 ; OR: 1.23 ; ctr: 0% ; resid: -0.1 ; n: 262">8%</td><td class="tx-r tx-num m2 tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: -19% ; ratio: ÷1.70 ; OR: 1/1.37 ; ctr: 25% ; resid: -23.4 ; n: 869">28%</td><td class="tx-r tx-num tx-br tx-bl tx-tot tx-b">100%<span class="tx-sec" style="font-weight:normal;"> ( 3 129)</span></td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">White</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +0% ; ratio: ×1.00 ; OR: 1.00 ; ctr: 0% ; resid: +0 ; n: 13">0%</td><td class="tx-r tx-num m1 tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: -4% ; ratio: ÷1.19 ; OR: 1/1.19 ; ctr: 10% ; resid: -24.2 ; n: 3 478">21%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: -1% ; ratio: ÷1.30 ; OR: 1/1.30 ; ctr: 3% ; resid: -11.4 ; n: 437">3%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +1% ; ratio: ×1.04 ; OR: 1.03 ; ctr: 0% ; resid: +4.2 ; n: 2 676">16%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +1% ; ratio: ×1.07 ; OR: 1.07 ; ctr: 1% ; resid: +5.5 ; n: 1 475">9%</td><td class="tx-r tx-num g1" data-toggle="tooltip" data-container="body" data-placement="auto right" title="diff: +4% ; ratio: ×1.08 ; OR: 1.07 ; ctr: 5% ; resid: +19.1 ; n: 8 316">51%</td><td class="tx-r tx-num tx-br tx-bl tx-tot tx-b">100%<span class="tx-sec" style="font-weight:normal;"> (16 395)</span></td></tr>
#> <tr class="tx-b tx-bt"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 17">0%</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 5 416">25%</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 743">3%</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 3 383">16%</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 1 807">8%</td><td class="tx-r tx-num tx-b" data-toggle="tooltip" data-container="body" data-placement="auto right" title="ref ; mean ctr: 6% ; n: 10 117">47%</td><td class="tx-r tx-num tx-br tx-bl tx-tot tx-b">100%<span class="tx-sec" style="font-weight:normal;"> (21 483)</span></td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">pvalue (Chi2 !)</td><td class="tx-r tx-num"><0.01%</td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num tx-br tx-bl tx-tot"></td></tr>
#> <tr class="tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Cramér's V</td><td class="tx-r tx-num">0.15</td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num"></td><td class="tx-r tx-num tx-br tx-bl tx-tot"></td></tr></tbody><tfoot><tr><td colspan="8"><div class="tx-foot">Contribution to Chi2: cell over-represented vs independence, by <span class="p1" style="font-weight:bold;">×1</span>; <span class="p2" style="font-weight:bold;">×2</span>; <span class="p3" style="font-weight:bold;">×5</span>; <span class="p4" style="font-weight:bold;">×10</span> the mean contribution; cell under-represented, by <span class="m1" style="font-weight:bold;">×1</span>; <span class="m2" style="font-weight:bold;">×2</span>; <span class="m3" style="font-weight:bold;">×5</span>; <span class="m4" style="font-weight:bold;">×10</span> the mean contribution.</div></td></tr></tfoot></table></div>

cars <- dplyr::rename(mtcars[1:7], weight = wt)
interpret(principal_component_analysis(cars, 1:7))
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-span" colspan="1"></th><th class="tx-span" colspan="3">Variables</th><th class="tx-span" colspan="3">Axe 1</th><th class="tx-span" colspan="3">Axe 2</th><th class="tx-span" colspan="3">Axe 3</th></tr><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">variable</th><th class="tx-r tx-num">mean</th><th class="tx-r tx-num">sd</th><th class="tx-r tx-num tx-br">sd/mean</th><th class="tx-r tx-num">coord</th><th class="tx-r tx-num">contrib</th><th class="tx-r tx-num tx-br">cos2</th><th class="tx-r tx-num">coord</th><th class="tx-r tx-num">contrib</th><th class="tx-r tx-num tx-br">cos2</th><th class="tx-r tx-num">coord</th><th class="tx-r tx-num">contrib</th><th class="tx-r tx-num tx-br">cos2</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-unit">&lt;sd&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;cv&gt;</th><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;row%&gt;</th><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;row%&gt;</th><th class="tx-r tx-num tx-unit">&lt;mean&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit">&lt;row%&gt;</th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">mpg</td><td class="tx-r tx-num g2">20.09</td><td class="tx-r tx-num g2">5.93</td><td class="tx-r tx-num tx-br g2">30%</td><td class="tx-r tx-num m4 tx-b">-0.93</td><td class="tx-r tx-num g2">17%</td><td class="tx-r tx-num tx-br g2">87%</td><td class="tx-r tx-num g1">-0.09</td><td class="tx-r tx-num g2">1%</td><td class="tx-r tx-num tx-br g2">1%</td><td class="tx-r tx-num m1 tx-b">-0.14</td><td class="tx-r tx-num g2">6%</td><td class="tx-r tx-num tx-br g2">2%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">cyl</td><td class="tx-r tx-num g2">6.19</td><td class="tx-r tx-num g2">1.76</td><td class="tx-r tx-num tx-br g2">28%</td><td class="tx-r tx-num p4 tx-b">0.96</td><td class="tx-r tx-num g2">18%</td><td class="tx-r tx-num tx-br g2">92%</td><td class="tx-r tx-num g1">-0.08</td><td class="tx-r tx-num g2">1%</td><td class="tx-r tx-num tx-br g2">1%</td><td class="tx-r tx-num m1 tx-b">-0.11</td><td class="tx-r tx-num g2">4%</td><td class="tx-r tx-num tx-br g2">1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">disp</td><td class="tx-r tx-num g2">230.72</td><td class="tx-r tx-num g2">121.99</td><td class="tx-r tx-num tx-br g2">53%</td><td class="tx-r tx-num p4 tx-b">0.95</td><td class="tx-r tx-num g2">18%</td><td class="tx-r tx-num tx-br g2">91%</td><td class="tx-r tx-num g1">0.09</td><td class="tx-r tx-num g2">1%</td><td class="tx-r tx-num tx-br g2">1%</td><td class="tx-r tx-num g1">0.07</td><td class="tx-r tx-num g2">1%</td><td class="tx-r tx-num tx-br g2">0%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">hp</td><td class="tx-r tx-num g2">146.69</td><td class="tx-r tx-num g2">67.48</td><td class="tx-r tx-num tx-br g2">46%</td><td class="tx-r tx-num p4 tx-b">0.87</td><td class="tx-r tx-num g2">15%</td><td class="tx-r tx-num tx-br g2">76%</td><td class="tx-r tx-num m2 tx-b">-0.36</td><td class="tx-r tx-num g2">11%</td><td class="tx-r tx-num tx-br g2">13%</td><td class="tx-r tx-num p1 tx-b">0.12</td><td class="tx-r tx-num g2">4%</td><td class="tx-r tx-num tx-br g2">1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">drat</td><td class="tx-r tx-num g2">3.60</td><td class="tx-r tx-num g2">0.53</td><td class="tx-r tx-num tx-br g2">15%</td><td class="tx-r tx-num m3 tx-b">-0.75</td><td class="tx-r tx-num g2">11%</td><td class="tx-r tx-num tx-br g2">56%</td><td class="tx-r tx-num m3 tx-b">-0.48</td><td class="tx-r tx-num g2">20%</td><td class="tx-r tx-num tx-br g2">23%</td><td class="tx-r tx-num p3 tx-b">0.44</td><td class="tx-r tx-num g2">57%</td><td class="tx-r tx-num tx-br g2">20%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">weight</td><td class="tx-r tx-num g2">3.22</td><td class="tx-r tx-num g2">0.96</td><td class="tx-r tx-num tx-br g2">30%</td><td class="tx-r tx-num p4 tx-b">0.88</td><td class="tx-r tx-num g2">15%</td><td class="tx-r tx-num tx-br g2">78%</td><td class="tx-r tx-num p2 tx-b">0.35</td><td class="tx-r tx-num g2">10%</td><td class="tx-r tx-num tx-br g2">12%</td><td class="tx-r tx-num p2 tx-b">0.26</td><td class="tx-r tx-num g2">19%</td><td class="tx-r tx-num tx-br g2">7%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">qsec</td><td class="tx-r tx-num g2">17.85</td><td class="tx-r tx-num g2">1.76</td><td class="tx-r tx-num tx-br g2">10%</td><td class="tx-r tx-num m3 tx-b">-0.54</td><td class="tx-r tx-num g2">6%</td><td class="tx-r tx-num tx-br g2">29%</td><td class="tx-r tx-num p4 tx-b">0.81</td><td class="tx-r tx-num g2">56%</td><td class="tx-r tx-num tx-br g2">65%</td><td class="tx-r tx-num p1 tx-b">0.17</td><td class="tx-r tx-num g2">9%</td><td class="tx-r tx-num tx-br g2">3%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num g2"></td><td class="tx-r tx-num tx-br g2"></td><td class="tx-r tx-num tx-b"></td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td><td class="tx-r tx-num tx-b"></td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td><td class="tx-r tx-num tx-b"></td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td></tr></tbody><tfoot><tr><td colspan="13"><div class="tx-foot">Coordinate on the axis, i.e. its correlation with it: a variable above, by <span class="p1" style="font-weight:bold;">+0.1</span>; <span class="p2" style="font-weight:bold;">+0.2</span>; <span class="p3" style="font-weight:bold;">+0.4</span>; <span class="p4" style="font-weight:bold;">+0.8</span> SD; a variable below, by <span class="m1" style="font-weight:bold;">-0.1</span>; <span class="m2" style="font-weight:bold;">-0.2</span>; <span class="m3" style="font-weight:bold;">-0.4</span>; <span class="m4" style="font-weight:bold;">-0.8</span> SD.<br><b>contrib</b>: its contribution to the variance of the axis; an axis sums to 100 %<br>cos2: quality of representation<br>sd/mean: coefficient of variation -- the standard deviation as a percentage of the mean, comparable between variables measured in different units</div></td></tr></tfoot></table></div>
#> <div class="tx-scrollbox"><table class="tabxplor-tab" data-quarto-disable-processing="true"><thead><tr><th class="tx-span" colspan="1"></th><th class="tx-span" colspan="3">Variance</th></tr><tr><th class="tx-l tx-br tx-bl tx-rv" rowspan="2">Axe</th><th class="tx-r tx-num">eigenvalue</th><th class="tx-r tx-num">% variance</th><th class="tx-r tx-num tx-br">cumul.</th></tr><tr><th class="tx-r tx-num tx-unit">&lt;var&gt;</th><th class="tx-r tx-num tx-unit">&lt;col%&gt;</th><th class="tx-r tx-num tx-br tx-unit"></th></tr></thead><tbody><tr><td class="tx-l tx-br tx-bl tx-rv">Axe 1</td><td class="tx-r tx-num g2">5.086</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:100%">72.7%</td><td class="tx-r tx-num tx-br g2">72.7%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 2</td><td class="tx-r tx-num g2">1.157</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:22.7%">16.5%</td><td class="tx-r tx-num tx-br g2">89.2%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 3</td><td class="tx-r tx-num g2">0.345</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:6.8%">4.9%</td><td class="tx-r tx-num tx-br g2">94.1%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 4</td><td class="tx-r tx-num g2">0.158</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:3.1%">2.3%</td><td class="tx-r tx-num tx-br g2">96.4%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 5</td><td class="tx-r tx-num g2">0.129</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:2.5%">1.8%</td><td class="tx-r tx-num tx-br g2">98.2%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 6</td><td class="tx-r tx-num g2">0.076</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:1.5%">1.1%</td><td class="tx-r tx-num tx-br g2">99.3%</td></tr>
#> <tr><td class="tx-l tx-br tx-bl tx-rv">Axe 7</td><td class="tx-r tx-num g2">0.049</td><td class="tx-r tx-num g2 tx-bar tx-bar-on" style="--tx-bar:1%">0.7%</td><td class="tx-r tx-num tx-br g2">100%</td></tr>
#> <tr class="tx-b tx-bt tx-bb tx-bb2"><td class="tx-l tx-br tx-bl tx-rv">Total</td><td class="tx-r tx-num g2">7.000</td><td class="tx-r tx-num tx-b">100%</td><td class="tx-r tx-num tx-br tx-b"></td></tr></tbody></table></div>
# }