Slider

En komponent, der viser sine børn i et diasshow eller en karrusel.

Indstillinger

• title | (string|node): titel for diasshowet/karrusellen, der skal vises øverst i toppen. Default: none.
• dots | boolean: visning af prikker i bunden for hurtigt at navigere til et dias. Default: true.
• fade | boolean: styrer, om der skal bruges fading til at skifte mellem dias. Default: false.
• draggable | boolean: styrer, om brugerne kan trække i dias for at navigere mellem dem. Default: false.
• pagination | string: om paginering skal vises enten øverst, nederst eller begge dele. Default: 'bottom'.
• goto | number: Hvis egenskaben ændres, springer komponenten til diaset med det valgte indeks. Default: 0.
• infinite | boolean: styrer, om diasshowet skal ombrydes omkring sit indhold. Default: false.
• interval | number: indstiller et tidsinterval for et automatisk diasskifte. Default: none.
• swipe | boolean: aktiverer træk/slæb-adfærd. Default: false.
• style | object: CSS inline-stilarter. Default: {}.
• onClick | function: callback, der påkaldes, når der klikkes på næste/forrige knapper. Default: onClick() {}.

Eksempler

• Minimal
• Customize Pagination
• Slideshow
• Custom Styling

Live Editor

<Slider title="Questions to explore:" > <p>Try generating new samples of the Normal data. You'll notice that the points don't always lie exactly on the line. This is typical variation. As you generate more random realizations of this plot you'll get better calibrated to the kind of deviation you can expect to see from this large a sample of Normal data.</p> <p>How do the normal qq plots change as you vary the df parameter for the t-distributed data?</p> <p>Can you tell just by looking at the t.data histograms that the data aren't normally distributed? Is it easier to tell from the QQ plots?</p> <p>How do the normal qq plots change as you vary the shape parameter in the gamma-distributed data?</p> </Slider>

<Slider title="Questions to explore:" >
    <p>Try generating new samples of the Normal data. You'll notice that the points don't always lie exactly on the line. This is typical variation. As you generate more random realizations of this plot you'll get better calibrated to the kind of deviation you can expect to see from this large a sample of Normal data.</p>
    <p>How do the normal qq plots change as you vary the df parameter for the t-distributed data?</p>
    <p>Can you tell just by looking at the t.data histograms that the data aren't normally distributed? Is it easier to tell from the QQ plots?</p>
    <p>How do the normal qq plots change as you vary the shape parameter in the gamma-distributed data?</p>
</Slider>

Resultat

ReferenceError: Provider is not defined