我正在使用R Studio，Plot_ly和Rmarkdown。
该网站是通过blogdown / blogdown_hugo建立的。
在数据框“ data_local_indices_m”中是列
“值”（具有每个日期的值，需要绘制），
“ data_date”（包含时间序列的日期），
“国家/地区”包含国家/地区名称（例如AUT）和
“大陆”（例如欧洲）。
我想要两个下拉菜单来更改绘制的图形：
第一个下拉列表应包含各大洲。 根据第一个下拉菜单中的选定值， 第二个下拉菜单应仅显示具有该值的国家/地区。
例如：
Dropdown1（大陆）：
-欧洲（已选择此值）
Dropdown2（国家/地区）：
-GER
-AUT
-ITA
...
我基本上有两个带有各自内容的下拉菜单，但我不知道如何使它们相互依赖。
此外，整个事物需要可变：
如果添加了一个新国家，它会自动出现（在下拉列表“国家”中，如果有新大陆，则应在下拉列表“大陆”中添加该内容）
设法使用相应的标签创建了两个下拉菜单，但它们并不相互依赖。
我只留下下面的代码。这是一种非常可悲的方法，但是它至少会创建下拉字段（彼此不依赖）。请随时提供一个更好的示例。也许将代码用作基本思想。
continents <- c("Africa", "Asia", "Australia", "Europe", "North America", "South America")
p2 <- Data_local_indices_m %>%
unnest(.sep = "_") %>%
mutate(data_date=as.yearmon(data_date)) %>%
select(country,data_date,IS_data_turb) %>%
plot_ly(
mode = 'lines',
x = ~data_date,
y = ~IS_data_turb,
transforms = list(
list(
type = 'filter',
target = ~country,
operation = '==',
value = unique(Data_local_indices_m$country)[1]))) %>%
layout(
updatemenus = list(list(
active = 3,
y = 0.9,
buttons = list(
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = continents[1]),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = continents[2]),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = continents[3]),
list(method = "restyle",
args = list("visible", list(TRUE, FALSE)),
label = continents[4]),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = continents[5]),
list(method = "restyle",
args = list("visible", list(FALSE, TRUE)),
label = continents[6]))),
list(
#active = 0,
y = 0.8,
x = -0.101,
buttons = list(
list(
method = "restyle",
args = list("transforms[0].value", unique(Data_local_indices_m$country)[1]),
label = unique(Data_local_indices_m$country)[1]),
list(method = "restyle",
args = list("transforms[0].value", unique(Data_local_indices_m$country)[2]),
label = unique(Data_local_indices_m$country)[2]),
list(method = "restyle",
args = list("transforms[0].value", unique(Data_local_indices_m$country)[3]),
label = unique(Data_local_indices_m$country)[3]),
list(method = "restyle",
args = list("transforms[0].value", unique(Data_local_indices_m$country)[4]),
label = unique(Data_local_indices_m$country)[4])
)
)
)
)
Dropdown1：“欧洲” 下拉菜单2：只有拥有“欧洲”大陆的可选国家/地区
->显示了相应国家/地区的图。
Packages in library ‘/home/rstudio-user/R/x86_64-pc-linux-gnu-library/3.6’:
anytime Anything to 'POSIXct' or 'Date' Converter
askpass Safe Password Entry for R, Git, and SSH
assertthat Easy Pre and Post Assertions
backports Reimplementations of Functions Introduced Since R-3.0.0
base64enc Tools for base64 encoding
BH Boost C++ Header Files
bitops Bitwise Operations
blogdown Create Blogs and Websites with R Markdown
bookdown Authoring Books and Technical Documents with R Markdown
Boom Bayesian Object Oriented Modeling
BoomSpikeSlab MCMC for Spike and Slab Regression
broom Convert Statistical Analysis Objects into Tidy Tibbles
bsts Bayesian Structural Time Series
callr Call R from R
cellranger Translate Spreadsheet Cell Ranges to Rows and Columns
cli Helpers for Developing Command Line Interfaces
clipr Read and Write from the System Clipboard
clisymbols Unicode Symbols at the R Prompt
colorspace A Toolbox for Manipulating and Assessing Colors and
Palettes
crayon Colored Terminal Output
crosstalk Inter-Widget Interactivity for HTML Widgets
cubature Adaptive Multivariate Integration over Hypercubes
curl A Modern and Flexible Web Client for R
data.table Extension of `data.frame`
DBI R Database Interface
dbplyr A 'dplyr' Back End for Databases
DEoptimR Differential Evolution Optimization in Pure R
desc Manipulate DESCRIPTION Files
devtools Tools to Make Developing R Packages Easier
digest Create Compact Hash Digests of R Objects
dplyr A Grammar of Data Manipulation
DT A Wrapper of the JavaScript Library 'DataTables'
ecodist Dissimilarity-Based Functions for Ecological Analysis
ellipsis Tools for Working with ...
energy E-Statistics: Multivariate Inference via the Energy of
Data
evaluate Parsing and Evaluation Tools that Provide More Details
than the Default
fansi ANSI Control Sequence Aware String Functions
fAssets Rmetrics - Analysing and Modelling Financial Assets
fBasics Rmetrics - Markets and Basic Statistics
fMultivar Rmetrics - Analysing and Modeling Multivariate
Financial Return Distributions
forcats Tools for Working with Categorical Variables (Factors)
forecast Forecasting Functions for Time Series and Linear Models
fracdiff Fractionally differenced ARIMA aka ARFIMA(p,d,q) models
fs Cross-Platform File System Operations Based on 'libuv'
generics Common S3 Generics not Provided by Base R Methods
Related to Model Fitting
ggplot2 Create Elegant Data Visualisations Using the Grammar of
Graphics
gh 'GitHub' 'API'
git2r Provides Access to Git Repositories
glue Interpreted String Literals
googleVis R Interface to Google Charts
gss General Smoothing Splines
gtable Arrange 'Grobs' in Tables
haven Import and Export 'SPSS', 'Stata' and 'SAS' Files
hexbin Hexagonal Binning Routines
highr Syntax Highlighting for R Source Code
hms Pretty Time of Day
htmltools Tools for HTML
htmlwidgets HTML Widgets for R
httpuv HTTP and WebSocket Server Library
httr Tools for Working with URLs and HTTP
igraph Network Analysis and Visualization
ini Read and Write '.ini' Files
jomo Multilevel Joint Modelling Multiple Imputation
jsonlite A Robust, High Performance JSON Parser and Generator
for R
knitr A General-Purpose Package for Dynamic Report Generation
in R
labeling Axis Labeling
later Utilities for Delaying Function Execution
lazyeval Lazy (Non-Standard) Evaluation
lme4 Linear Mixed-Effects Models using 'Eigen' and S4
lmtest Testing Linear Regression Models
lubridate Make Dealing with Dates a Little Easier
magrittr A Forward-Pipe Operator for R
mailR A Utility to Send Emails from R
markdown 'Markdown' Rendering for R
memoise Memoisation of Functions
mice Multivariate Imputation by Chained Equations
mime Map Filenames to MIME Types
minqa Derivative-free optimization algorithms by quadratic
approximation
mitml Tools for Multiple Imputation in Multilevel Modeling
mnormt The Multivariate Normal and t Distributions
modelr Modelling Functions that Work with the Pipe
munsell Utilities for Using Munsell Colours
mvnormtest Normality test for multivariate variables
mvtnorm Multivariate Normal and t Distributions
nleqslv Solve Systems of Nonlinear Equations
nloptr R Interface to NLopt
numDeriv Accurate Numerical Derivatives
OECD Search and Extract Data from the OECD
openssl Toolkit for Encryption, Signatures and Certificates
Based on OpenSSL
ordinal Regression Models for Ordinal Data
pacman Package Management Tool
padr Quickly Get Datetime Data Ready for Analysis
pan Multiple Imputation for Multivariate Panel or Clustered
Data
PerformanceAnalytics Econometric Tools for Performance and Risk Analysis
pillar Coloured Formatting for Columns
pkgbuild Find Tools Needed to Build R Packages
pkgconfig Private Configuration for 'R' Packages
pkgload Simulate Package Installation and Attach
plogr The 'plog' C++ Logging Library
plotly Create Interactive Web Graphics via 'plotly.js'
plyr Tools for Splitting, Applying and Combining Data
prettyunits Pretty, Human Readable Formatting of Quantities
processx Execute and Control System Processes
progress Terminal Progress Bars
promises Abstractions for Promise-Based Asynchronous Programming
ps List, Query, Manipulate System Processes
purrr Functional Programming Tools
quadprog Functions to Solve Quadratic Programming Problems
Quandl API Wrapper for Quandl.com
quantmod Quantitative Financial Modelling Framework
R.methodsS3 S3 Methods Simplified
R.oo R Object-Oriented Programming with or without
References
R.utils Various Programming Utilities
R6 Encapsulated Classes with Reference Semantics
RApiDatetime R API Datetime
rcmdcheck Run 'R CMD check' from 'R' and Capture Results
RColorBrewer ColorBrewer Palettes
Rcpp Seamless R and C++ Integration
RcppEigen 'Rcpp' Integration for the 'Eigen' Templated Linear
Algebra Library
RCurl General Network (HTTP/FTP/...) Client Interface for R
readr Read Rectangular Text Data
readxl Read Excel Files
rematch Match Regular Expressions with a Nicer 'API'
remotes R Package Installation from Remote Repositories,
Including 'GitHub'
reprex Prepare Reproducible Example Code via the Clipboard
reshape2 Flexibly Reshape Data: A Reboot of the Reshape Package
rJava Low-Level R to Java Interface
RJSONIO Serialize R Objects to JSON, JavaScript Object Notation
rlang Functions for Base Types and Core R and 'Tidyverse'
Features
rmarkdown Dynamic Documents for R
robustbase Basic Robust Statistics
rprojroot Finding Files in Project Subdirectories
rsdmx Tools for Reading SDMX Data and Metadata
rstudioapi Safely Access the RStudio API
rvest Easily Harvest (Scrape) Web Pages
scales Scale Functions for Visualization
selectr Translate CSS Selectors to XPath Expressions
servr A Simple HTTP Server to Serve Static Files or Dynamic
Documents
sessioninfo R Session Information
shiny Web Application Framework for R
sn The Skew-Normal and Related Distributions Such as the
Skew-t
sourcetools Tools for Reading, Tokenizing and Parsing R Code
stabledist Stable Distribution Functions
stringi Character String Processing Facilities
stringr Simple, Consistent Wrappers for Common String
Operations
sys Powerful and Reliable Tools for Running System Commands
in R
tibble Simple Data Frames
tidyquant Tidy Quantitative Financial Analysis
tidyr Easily Tidy Data with 'spread()' and 'gather()'
Functions
tidyselect Select from a Set of Strings
tidyverse Easily Install and Load the 'Tidyverse'
timeDate Rmetrics - Chronological and Calendar Objects
timeSeries Rmetrics - Financial Time Series Objects
timetk A Tool Kit for Working with Time Series in R
tinytex Helper Functions to Install and Maintain 'TeX Live',
and Compile 'LaTeX' Documents
tseries Time Series Analysis and Computational Finance
tsibble Tidy Temporal Data Frames and Tools
TTR Technical Trading Rules
ucminf General-Purpose Unconstrained Non-Linear Optimization
uncertaintymeasures Functions to create uncertainty measures using
turbulence
urca Unit Root and Cointegration Tests for Time Series Data
usethis Automate Package and Project Setup
utf8 Unicode Text Processing
vctrs Vector Helpers
viridisLite Default Color Maps from 'matplotlib' (Lite Version)
whisker {{mustache}} for R, logicless templating
withr Run Code 'With' Temporarily Modified Global State
xfun Miscellaneous Functions by 'Yihui Xie'
XML Tools for Parsing and Generating XML Within R and
S-Plus
xml2 Parse XML
xopen Open System Files, 'URLs', Anything
xtable Export Tables to LaTeX or HTML
xts eXtensible Time Series
yaml Methods to Convert R Data to YAML and Back
zeallot Multiple, Unpacking, and Destructuring Assignment
zoo S3 Infrastructure for Regular and Irregular Time Series
(Z's Ordered Observations)
Packages in library ‘/opt/R/3.6.0/lib/R/library’:
base The R Base Package
boot Bootstrap Functions (Originally by Angelo Canty for S)
class Functions for Classification
cluster "Finding Groups in Data": Cluster Analysis Extended
Rousseeuw et al.
codetools Code Analysis Tools for R
compiler The R Compiler Package
datasets The R Datasets Package
foreign Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS',
'Stata', 'Systat', 'Weka', 'dBase', ...
graphics The R Graphics Package
grDevices The R Graphics Devices and Support for Colours and
Fonts
grid The Grid Graphics Package
KernSmooth Functions for Kernel Smoothing Supporting Wand & Jones
(1995)
lattice Trellis Graphics for R
MASS Support Functions and Datasets for Venables and
Ripley's MASS
Matrix Sparse and Dense Matrix Classes and Methods
methods Formal Methods and Classes
mgcv Mixed GAM Computation Vehicle with Automatic Smoothness
Estimation
nlme Linear and Nonlinear Mixed Effects Models
nnet Feed-Forward Neural Networks and Multinomial Log-Linear
Models
parallel Support for Parallel computation in R
rpart Recursive Partitioning and Regression Trees
spatial Functions for Kriging and Point Pattern Analysis
splines Regression Spline Functions and Classes
stats The R Stats Package
stats4 Statistical Functions using S4 Classes
survival Survival Analysis
tcltk Tcl/Tk Interface
tools Tools for Package Development
utils The R Utils Package
答案 0 :(得分：0)
您的代码确实很大。我将用一个简单的例子来说明这个想法。
您可以临时保存所选的大陆。之后，您只能选择与所选大洲相对应的国家/地区，因此在secound下拉菜单中只能在正确的国家/地区之间进行选择。像这样：
# some data
df <- data.frame(continent= c("europe", "europe", "asia", "asia"), country= c("italy", "germany", "china", "india"))
df
continent country
1 europe italy
2 europe germany
3 asia china
4 asia india
# now choose some continent (you will make this as a dropdown menu)
continent_choosen <- "europe"
# choosing from the possible countries
df$country[df$continent == continent_choosen]
italy germany
对于可能的城市或可能的郊区等都存在相同的想法。