我想在我正在编写的包中包含一个示例数据集(Twitter推文和metadata)R.
我使用Twitter API它下载了一个示例data.frame,并将其保存为我的包中的.RData(带有相应的.R数据描述文件).
当我运行R CMDCheck时,我得到以下注意,
* checking data for non-ASCII characters ... NOTE
Note: found 287 marked UTF-8 strings
我试图保存data.frame有ASCII=TRUE,希望这将解决这个问题.但它仍然存在.有关如何让R CMDCHECK在没有音符的情况下运行的任何想法？
(另外,UTF-8如果这是解决方案,我愿意从示例数据中删除所有标记的字符串).谢谢!
data.frame中的示例行:
First time in SF (@ San Francisco International Airport (SFO) - @flysfo in San Francisco, CA) https://t.co/1245xqxtwesr
favorited favoriteCount replyToSN created truncated replyToSID id replyToUID
1 FALSE 0 <NA> 2015-03-13 23:30:35 FALSE <NA> 576525795927179264 <NA> …实际上我担心数据,它是如何来的,在不同的矢量类型.某些列最初是整数或数字类型,但显示为字符类型.
如果我通过read.csv()它读取数据帧,它会猜测哪种类型的向量并自动转换它们.我找不到同样的fread()和data.table().数据附在此处
structure(list(V1 = c("1", "2", "3", "4", "5", "6"), ID = c("109",
"110", "111", "112", "113", "114"), SignalIntensity = c(7.58043495940162,
11.2698560261255, 8.60063586764357, 9.54355755391806, 10.1812351379984,
8.11689493952339), SNR = c(1.34218273720186, 9.75097840763912,
1.80485348504829, 3.20137685049428, 4.64599368338536, 1.42263609838542
)), .Names = c("V1", "ID", "SignalIntensity", "SNR"), row.names = c(NA,
6L), class = "data.frame")
当我用read.csv()读取数据帧时
str(df)
data.frame': 20469 obs. of 4 variables:
$ X : int 1 2 3 4 5 6 7 8 9 10 ...
$ ID : …我试图寻找向量元素在另一个向量中的位置.在这里,我有兴趣尽快使用实现binary search.我有不同的长度为100万或更多的向量,所以我想要更快地实现某些目标.
在我的情况下以下情况:
1) vector我在搜索中进行排序.
2)我正在搜索的元素将永远存在,即我没有一个案例not found,我想以更快的方式获得向量元素的索引.
我尝试了以下代码来获取向量元素的索引.
#include <iostream>
#include <vector>
#include <algorithm>
template<class Iter, class T>
Iter binary_find(Iter begin, Iter end, T val)
{
Iter i = std::lower_bound(begin, end, val);
return i;
}
int main() {
std::vector<std::string> values = {"AAAAAA","AB", "AD" ,"BCD","CD", "DD" };
std::vector<std::string> tests = {"AB", "CD","AD", "DD"};
for(int i=0 ; i < tests.size(); i++) {
int pos = binary_find(values.begin(), values.end(), tests.at(i))- values.begin();
std::cout << tests.at(i) << " found at: …我想为我闪亮的应用程序提供动态标签.我尝试了下面的代码
## app.R ##
library(shiny)
library(shinydashboard)
ui <- dashboardPage(
dashboardHeader(),
dashboardSidebar(
checkboxGroupInput("Tabs",
label = h4("tabpanel"),
choices = list("tabs" = "tabs"),
selected = NULL),
checkboxGroupInput("moreTabs",
label = h4("moretabpanel"),
choices = list("moretabs" = "moretabs"),
selected = NULL)
),
dashboardBody(
conditionalPanel(
condition = "input.Tabs == 'tabs'",
tabBox(
title = "intro",
id= "ttabs", width = 8, height = "420px",
tabPanel("Files", dataTableOutput("Files")),
conditionalPanel(
condition = "input.moreTabs == 'moretabs'",
tabPanel("Files1", dataTableOutput("Files1"))
)
)
)
)
)
server <- function(input, output) { }
shinyApp(ui, server)
但是,我没有成功动态使用选项卡面板.它只显示一个选项卡,在检查时,它应该显示第二个选项卡.
当我用ansible复制文件时备份文件(写入backup = yes).我的问题是关于由ansible创建的默认文件名.
config.xml.6634.2018-05-22@17:52:12~
6634在这个文件名中的含义是什么？
我绝对不是mvn的专家,但经过2天的黑客攻击,我只是放弃了.
我的工作流程
1.
mvn archetype:generate
-DarchetypeGroupId=org.apache.flink
-DarchetypeArtifactId=flink-quickstart-scala
-DarchetypeVersion=0.10.1
-DgroupId=org.apache.flink.quickstart
-DartifactId=flink-scala-project
-Dversion=0.1
-Dpackage=org.apache.flink.quickstart
-DinteractiveMode=false
2.
cd flink-scala-project
3.
mvn clean package
这是一个构建log: https://gist.github.com/zavalit/1e78478ebdda827f3454,当我运行
`java -jar target/flink-scala-project-0.1.jar`
我明白了
Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/flink/api/scala/ExecutionEnvironment$
at org.apache.flink.quickstart.Job$.main(Job.scala:41)
at org.apache.flink.quickstart.Job.main(Job.scala)
Caused by: java.lang.ClassNotFoundException: org.apache.flink.api.scala.ExecutionEnvironment$
at java.net.URLClassLoader$1.run(URLClassLoader.java:366)
at java.net.URLClassLoader$1.run(URLClassLoader.java:355)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:354)
at java.lang.ClassLoader.loadClass(ClassLoader.java:425)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:308)
at java.lang.ClassLoader.loadClass(ClassLoader.java:358)
... 2 more
我有一个50,000行的data.frame,有一些重复,我想删除.
SYMBOL INTENSITY CALL VALUE
1 DDR1 2464.3023 P 0.00016023613
2 RFC2 496.5190 P 0.0193034606
3 HSPA6 733.4763 P 0.0008046637
4 PAX8 2138.2882 P 0.0005617505
5 GUCA1A 176.3272 A 0.1896873022
6 UBA7 729.6157 P 0.0170004527
7 DDR1 2464.3023 P 0.0016023613
8 RFC2 496.5190 P 0.0593034606
9 HSPA9 733.4763 P 0.0008046637
10 PAX8 2138.2882 P 0.15617505
11 GUCA1A2 176.3272 A 0.01896873022
12 UBA8 729.6157 P 0.0170004527
我用以下来删除重复项.我在第四栏中保留了最小的"VALUE".
dt <- data.table(df)
WoDuplic <- dt[,.SD[which.min(VALUE)],by=list(SYMBOL)]
它用于此目的,但速度非常慢,从上一维度的data.frame中删除重复项需要大约10秒钟.有没有办法让这个过程更快？
编辑:输出看起来像
SYMBOL INTENSITY CALL VALUE
1 …我正在尝试一个小巧的应用程序,其中我从本地目录加载CSV文件,然后从数据框中选择特定列,并使用此子集化数据框进行进一步的数据分析.
library(shiny)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
titlePanel("Old Faithful Geyser Data"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
fileInput("dataset", "Choose CSV File",
multiple = TRUE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Include clarifying text ----
#helpText(em("Note: This app requires file in csv format only!!")),
helpText(em("Note:Select all the inputs and click on button as given below to exectute the app")),
# Input: Checkbox if file has …我想检查数组中的size()数字或数字.rowsstd::vector()
我有矢量
std::vector<int> vec[3];
vec.size() 不适用于上面的矢量声明.
我尝试为NLP任务安装YamCha工具,如NER,POS和分块.
在尝试安装时,我按照安装步骤进行操作
% ./configure
% make
% make check
% su
# make install
我收到以下错误消息: -
param.cpp:在成员函数'bool YamCha :: Param :: open(int,char**,const YamCha :: Option*)':param.cpp:102:42:error:'strlen'未在此声明scope size_t nlen = strlen(opts [i] .name); ^ param.cpp:103:68:错误:'strncmp'未在此范围内声明if(nlen == len && strncmp(&argv [ind] [2],opts [i] .name,len)== 0) {^ param.cpp:在成员函数'bool YamCha :: Param :: open(const char*,const YamCha :: Option*)':param.cpp:182:28:error:'strncpy'未在此声明scope strncpy(str,arg,1024); ^ param.cpp:185:12:警告:不推荐使用从字符串常量转换为'char*'[-Wwrite-strings] make all-recursive make 1:进入目录
/home/hamada/Documents/YamCha/yamcha-0.33' Making all in src make[2]: Entering directory/home/hamada/Documents/YamCha/yamcha-0.33/src '/ bin/bash ../libtool --mode = compile --tag = …