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df <- read.csv('https://raw.githubusercontent.com/BlankerL/DXY-2019-nCoV-Data/master/csv/DXYArea.csv')

bj <- df[df$provinceName == '北京市',]
plot(bj$province_confirmedCount~as.Date(bj$updateTime))

sh <- df[df$provinceName == '上海市',]
plot(sh$province_confirmedCount~as.Date(sh$updateTime))

sz <- df[df$cityName == '深圳',]
plot(sz$city_confirmedCount~as.Date(sz$updateTime))

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.markdown-here-wrapper {
  font-size: 16px;
  line-height: 1.8em;
  letter-spacing: 0.02em;
  font-family: 微软雅黑;
}


pre, code {
  font-size: 14px;

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library(tidyverse)
hmdb <- read_csv('hmdb.csv')
hmdb$iupac_name <- gsub( "b'", "", as.character(hmdb$iupac_name))
hmdb$iupac_name <- gsub( "'$", "", as.character(hmdb$iupac_name))
hmdb$name <- gsub( "b'", "", as.character(hmdb$name))
hmdb$name <- gsub( "'$", "", as.character(hmdb$name))
hmdb$omim <- gsub( "^\\[", "", as.character(hmdb$omim))
hmdb$omim <- gsub( "]$", "", as.character(hmdb$omim))
hmdb$dname <- gsub( "^\\[", "", as.character(hmdb$dname))
hmdb$dname <- gsub( "]$", "", as.character(hmdb$dname))

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t3db <- read_csv("t3db.csv")
t3db$iupac_name <- gsub( "b'", "", as.character(t3db$iupac_name))
t3db$iupac_name <- gsub( "'$", "", as.character(t3db$iupac_name))

t3db$name <- gsub( "b'", "", as.character(t3db$name))
t3db$name <- gsub( "'$", "", as.character(t3db$name))

t3db$InChIKey <- gsub( "InChIKey=", "", as.character(t3db$InChIKey))
write.csv(t3db,file = 't3dbnew.csv')

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library('stringr')
library('readr')
library('rcrossref')

doiref <- function(path, style = 'apa'){
  mystring <- readr::read_file(path)
  doi <- unlist(stringr::str_extract_all(mystring, "\\b10\\.(\\d+\\.*)+[\\/](([^\\s\\.])+\\.*)+\\b"))
  doi <- unique(doi)
  ref <- vector()
  for (i in 1:length(doi)){

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library(tidypvals)
library(dplyr)
library(ggplot2)
aj1 = anti_join(head2015,chavalarias2016)
aj2 = anti_join(chavalarias2016,head2015)
sj1 = semi_join(head2015,chavalarias2016)
allp = rbind(aj1,aj2,sj1)

allp = rbind(allp,brodeur2016)