r data processing and plotting summary echart

# Read Excel
1) readxl package
library (readxl)

path<-"D:\\xiangmu\\lixueyuan\\data1.xls"
data<-read_excel(path,range="A1:BU221")

2) the data bit count and a column format dataframe

as.data.frame(table(data$性别)) ##进行计数

3) The count display and a ratio of the bracketed

label_value <- paste('(', round(df$nums/sum(df$nums) * 100, 1), '%)', sep = '')

Results:
"(53.2%)" "(46.8%)"
will be added to the tag sex

label <- paste(df$type, label_value, sep = '')

Result: The
"male (53.2%)," "female (46.8%)."

4) Figure gender proportion yourselves and present information

ggplot(data=df, aes(x="性别",y=nums,fill=type))+
  geom_bar(width = 7,stat ="identity")+   ##width用来调整文本与圆环大小
  coord_polar("y", start=0)+
    scale_fill_manual(values=c('#FE8463', '#60C0DD' ))+   ##对原有填充颜色进行改变
  labs(x = '', y = '', title = '')+
  theme(axis.ticks = element_blank())+
  theme(axis.text.x = element_blank()) +
  theme(legend.position = "none") +
    theme(panel.background = element_rect(fill='white', colour='pink'))+  ##调整图片背景颜色与背景边框颜色
  geom_text(aes(y = df$nums/2 + c(0, cumsum(df$nums)[-length(df$nums)]), x = sum(df$nums)/3500, label = label),size=4,color='white')  ##文本显示 男女比例

5) draw a map with rechart

city <-c('安徽','福建','甘肃','广东','广西','贵州','河北','河南','湖北','湖南','江苏','江西','辽宁','内蒙古','山东','山西','陕西','四川', '新疆','云南','浙江','重庆')
as.character(city)
value<-c(101,40,60,35, 105, 150,  50, 110,  39,  35,  25, 80, 15,  20,  40,  66,  35,  80,  25,  67,  150,0)
as.character(value)
cdata <- data.frame(city,value)
library(devtools)
install_github('lchiffon/REmap')
library(REmap)
library(recharts)
a<-data.frame('浙江省',121.56,29.8)
echartr(cdata,city, value, type='map_china')%>%
  setDataRange(splitNumber=0, valueRange=range(0,150), 
               color=c('red','orange','pink')) %>% 
  setToolbox(show = FALSE)%>%
  setLegend(show = FALSE)%>%
  setTitle(title='萌新地区分布图', pos=12,
           textStyle=textStyle(fontFamily='Courier New', fontSize=24))%>%
  addMP(
    series="浙江",
    data=data.frame(name='浙江省',value=2426),
    symbol ='emptyCircle',
    symbolSize=10,
    effect = list(show=T))%>%
  addGeoCoord(a)

But it has not displayed directly provinces and the number
and use mapping can show the number of pages echart
https://echarts.baidu.com/echarts2/doc/example.html

6) Figure painting echart
students distributed

xueyuan<-as.data.frame(table(data$`专业名称（匹配）`))
View(xueyuan)
names(xueyuan)<-c('学院','人数')
echartr(xueyuan,学院,人数)

7) surname word cloud

library(stringr)
xingshi<-str_sub(data$姓名, 1, 1)
xingshi<-as.data.frame(table(xingshi))
library(wordcloud2)
wordcloud2(xingshi, size = 1, minSize = 0, gridSize =  0,
           fontFamily = 'Segoe UI', fontWeight = 'bold',
           color = 'random-dark', backgroundColor = "pink",
           minRotation = -pi/4, maxRotation = pi/4, shuffle = TRUE,
           rotateRatio = 0.4, shape = 'star', ellipticity = 0.65,
           widgetsize = NULL, figPath = NULL, hoverFunction = NULL)

And a echart do some nice FIG

color scheme: '# C1232B', '# B5C334', '# FCCE10', '# E87C25', '# 27727B',
'# FE8463', '# 9BCA63', '# FAD860' , '# F3A43B', '# 60C0DD',
'# D7504B', '# C6E579', '# F4E001', '# F0805A', '# 26C0C0'

The effect of moving map Cai million recorded using the master screen moving map display and do pr

8) information filtering, choose a column containing a word

data1<-data%>% 
  filter(考生特长 %in% '舞')