用图，RMD过滤派图

Question

我在过滤饼图方面有问题。 基本上，我现在拥有的代码为我过滤的每个值创建了所有不同图表的列表。

regPlotsA<-map(unique(SpLC1721A$Reg), ~SpLC1721A%>%
                filter(Reg==.x ) %>%
                plot_ly(labels = ~variable, values = ~value, type = 'pie', frame=~Anno)%>%
                layout(title = .x ,
                       xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
                       yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))%>%
                 animation_opts(
                   redraw = FALSE, frame =3000, transition= 2900
                 )
)

我需要做的是将此代码转换为下拉列表的内容，用户可以从中选择针对特定reg值观察到的数据，然后绘制相对图形。 我显然不能在sarkdown文件上做这样的事情，在 ioslides 演示中，我感到很愚蠢。

[我正在处理的数据] [1]

structure(list(X = c("Piemonte", "Valle d'Aosta / Vallée d'Aoste", 
"Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", "Veneto", 
"Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", "Umbria", 
"Marche", "Lazio", "Abruzzo", "Molise", "Campania", "Puglia", 
"Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna", "Piemonte", 
"Valle d'Aosta / Vallée d'Aoste", "Liguria", "Lombardia", "Trentino Alto Adige / Südtirol", 
"Veneto", "Friuli-Venezia Giulia", "Emilia-Romagna", "Toscana", 
"Umbria", "Marche", "Lazio", "Abruzzo", "Molise", "Campania", 
"Puglia", "Basilicata", "Calabria", "Sicilia", "Sardegna"), variable = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("vanno.a.piedi", "usano.mezzi.di.trasporto"
), class = "factor"), value = c(13.8, 16.4, 16.2, 8.6, 17.6, 
8.8, 10.2, 9.9, 12.1, 6.9, 7.9, 11.8, 11, 16.3, 18.2, 18, 17.3, 
12.7, 13, 14.8, 84.2, 82.5, 83.5, 89.5, 82.2, 90.6, 89.1, 89.4, 
87.1, 91.7, 91.4, 86.9, 87.8, 82.6, 80.1, 81, 81.8, 85.9, 85.8, 
84.9, 14.3, 21.3, 14.1, 10.3, 14.9, 10.3, 11, 10.9, 11, 9.5, 
9.8, 10.6, 12.6, 13.4, 17.4, 16.5, 13.7, 15.1, 15.4, 12.9, 84.8, 
77.4, 85, 88.7, 84.6, 88.9, 88, 88.7, 87.7, 89.5, 89.3, 87.1, 
86.4, 85.4, 80.6, 81.9, 83.4, 84, 83.3, 86.2, 11.8, 19.9, 17, 
10.5, 15.9, 9.4, 12.1, 9.9, 11.3, 10.8, 10.7, 11.2, 7.7, 13.4, 
17.1, 15.7, 14, 12.6, 12.8, 14.9, 88.2, 80.1, 83, 89.4, 84.1, 
90.6, 87.9, 90.1, 88.7, 89.2, 89.3, 88.8, 92.3, 86.6, 82.9, 84.3, 
86, 87.4, 87.2, 85.1, 12.1, 19.7, 14.4, 9.6, 19, 6.4, 9, 9.7, 
10.7, 9, 11, 9.5, 13.2, 12.5, 20.3, 14.2, 12.8, 16.6, 13.3, 14.9, 
87.9, 80.3, 85.6, 90.4, 81, 93.6, 91, 90.3, 89.3, 91, 89, 90.5, 
86.8, 87.5, 79.7, 85.8, 87.2, 83.4, 86.7, 85.1, 15.1, 20.4, 15.8, 
12.1, 14.2, 7.3, 8.2, 10.7, 9.8, 10.9, 9.4, 11.5, 13.8, 13.7, 
17.2, 17, 15.5, 14, 11.6, 13.1, 84.9, 79.6, 84.2, 87.9, 85.8, 
92.7, 91.8, 89.3, 90.2, 89.1, 90.6, 88.5, 86.2, 86.3, 82.8, 83, 
84.5, 86, 88.4, 86.9), Anno = c(2017, 2017, 2017, 2017, 2017, 
2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 
2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 
2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 2017, 
2017, 2017, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2019, 2019, 
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
2019, 2019, 2019, 2019, 2019, 2020, 2020, 2020, 2020, 2020, 2020, 
2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 
2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 
2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 2020, 
2020, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 
2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 
2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021, 
2021, 2021, 2021, 2021, 2021, 2021, 2021, 2021)), row.names = c(NA, 
-200L), class = "data.frame")

Answer 1

根据您的评论，

我假设您的x dput 输出的列应该是您要过滤的reg之上。我将名称更改为reg此答案。

这是您可以完成这项工作的众多方法之一。您可以使用绘图来进行此下拉。但是，如果您使用的是RMD，我发现使用可用的许多其他工具更容易。

这使用了软件包shinyrpg，但这不是闪亮的运行时（或与闪亮应用程序有关的任何内容）。我很确定这仍然不是克兰包装。您可以使用devTools :: install_github（“ Rinterface/Shinyrpg”）获得此库。

我首先创建样式标签以隐藏所有图，并在下拉菜单和图之间添加一些空间。更改可见性可确保最初只用一个图加载。 （与代码的其余部分结合使用时。）然后，我创建下拉菜单并附加一个换事事件。

<style>
.js-plotly-plot {
  display: none;
  margin: 20px;
}
</style>


```{r dropdown}
library(shinyRPG)
# create a dropdown menu to change the visibility
tagDrop  <- rpgSelect("piePlot", "Choose a Pie Chart to Visualize", 
                      setNames(LETTERS[1:length(unique(SpLC1721A$Reg))],
                               unique(SpLC1721A$Reg)),
                      multiple = F)
tagDrop$children[[2]]$attribs$onchange <- "getOps(this)"
tagDrop

```

接下来，我添加了图形。

```{r plotters,results='asis'}

htmltools::tagList(map(unique(SpLC1721A$Reg), ~SpLC1721A %>%
                         filter(Reg == .x ) %>%
                         plot_ly(labels = ~variable, values = ~value, 
                                 type = 'pie', frame = ~Anno)%>%
                         layout(title = .x ,
                                xaxis = list(showgrid = FALSE, zeroline = FALSE,
                                             showticklabels = FALSE),
                                yaxis = list(showgrid = FALSE, zeroline = FALSE,
                                             showticklabels = FALSE))%>%
                         animation_opts(
                           redraw = FALSE, frame =3000, transition= 2900
                         )
))

```

最后，我编写了确保第一个绘图可见的代码，并在JavaScript中进行了对事件。如果您运行此块，则不会做任何事情。您必须编织才能执行JS。

```{r pickMe,results='asis',engine='js'}
// for the initial load; show only one pie
setTimeout(function() {
  picker = document.querySelectorAll('.js-plotly-plot');
  picker[0].style.display = 'block';
})

// Something selected by user triggers this function
function getOps(sel) {   
  //get ref to select list and display text box
  graphy = document.querySelectorAll('.js-plotly-plot');
  // loop through selections
  for(i = 0; i < sel.length; i++) {
    opt = sel.options[i];
    if ( opt.selected ) {
      graphy[i].style.display = 'block';
    } else {
      graphy[i].style.display = 'none';
    }
  }
}

```