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![Appendix
1. The data were collected from January, 2011 to February, 2015 from China Labour Bulletin
(http://maps.clb.org.hk/strikes/en). Data were recorded as monthly and saved in Excel spreadsheet
format. Two data sets (labour.csv and labour.alt.csv) were then generated by R codes to created plots in
Tableau.
# Project 01
#install.packages("xlsx", dependencies=TRUE)
#install.packages("lubridate", dependencies=TRUE)
#install.packages("zoo")
library(xlsx)
library(lubridate)
library(zoo)
# 1a.
strikes = read.xlsx("I:/STAT6610/Homework/project1/proj01_strikes.xlsx", sheetName="Labour",
as.data.frame=TRUE,header=TRUE)
# calculate strikes by year by locations
# This is to make one plot with all four Locations on the time plot in different colors.
# Also for dynamic bubble graph and stacked up bar graph.
year=rep(c("2011/12/31","2012/12/31","2013/12/31","2014/12/31", "2015/02/28"),4)
locations=rep(c("Beijing","Chongqing","Guangdong","Shanghai"),each=5)
num_strikes=numeric(length(year))
for (i in 1:length(year))
{
num_strikes[i]=sum(strikes$Strikes[which(year(strikes$Date)==year(year[i])
& (strikes$Locations==locations[i]))])
}
labour=data.frame(year, locations, num_strikes)
write.csv(labour, "I:/STAT6610/Homework/project1/labour.csv",row.names=FALSE )
# create another data set for individual bar graph and cluster bar graph
Year=c("2011/12/31","2012/12/31","2013/12/31","2014/12/31", "2015/02/28")
Beijing=num_strikes[1:5]
Chongqing=num_strikes[6:10]
Guangdong=num_strikes[11:15]
Shanghai=num_strikes[16:20]
labour.alt=data.frame(Year,Beijing,Chongqing,Guangdong,Shanghai)
write.csv(labour.alt, "I:/STAT6610/Homework/project1/labour.alt.csv",row.names=FALSE)](https://image.slidesharecdn.com/d5018e03-2e13-4c94-bd7b-0dbd39a47e79-150316234912-conversion-gate01/85/proj_plots-11-320.jpg)
proj_plots
- 1. Stat. 4868/6610 DataVisualization Name: ___Christina Huang________ Department of Statistics and Biostatistics (print First Last ) CSU East Bay Class Number:___STAT 6610________ Source: January, 2011 to February, 2015 from China Labour Bulletin website. 1. b. The time plot for each Location by Tableau China Labour Strikes (2011-2015) Beijing Labour Strikes 2011-2015 Chongqing Labour Strikes 2011-2015 Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 2011 2012 2013 2014 2015 Year 0 5 10 15 20
- 2. China Labour Strikes(2011-2015) Beijing Labour Strikes 2011-2015 Chongqing Labour Strikes 2011-2015 Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 2011 2012 2013 2014 2015 Year 0 5 10 15 20 China Labour Strikes (2011-2015) Beijing Labour Strikes 2011-2015 Chongqing Labour Strikes 2011-2015 Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 2011 2012 2013 2014 2015 Year 0 50 100 150 200 250 300
- 3. 1. c. Nneplot with all four Locations on the time plot in different colors by Tableau China Labour Strikes (2011-2015) Chongqing Labour Strikes 2011-2015 Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 2011 2012 2013 2014 2015 Year 0 10 20 30 40 China Labour Strikes (2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 2011 2012 2013 2014 2015 Year 0 50 100 150 200 250 300 Shanghai Guangdong Locations Beijing Chongqing Guangdong Shanghai
- 4. 1. d. Theclustered bar graph for the data by Tableau. Optional stacked up bar graph: China Labour Strikes (2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Year 2011 2012 2013 2014 2015 0 50 100 150 200 250 300 54 642 154 12 5 2 243 13 10 11 301 20 44 22 42 5 86 Measure Names Beijing Chongqing Guangdong Shanghai
- 5. 1. e. Thescreen shots of each year from the dynamic bubble graph by Tableau are show below: China Labour Strikes (2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Guangdong 54 Shanghai 6 Beijing 2 Locations Beijing Chongqing Guangdong Shanghai Num Strikes 2 100 200 301 Year of Year 2011 Show History China Labour Strikes (2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Beijing 5 Locations Beijing Chongqing Guangdong Shanghai Num Strikes 2 100 200 301 Year of Year 2012 Show History
- 6. China Labour Strikes(2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Beijing 13 Locations Beijing Chongqing Guangdong Shanghai Num Strikes 2 100 200 301 Year of Year 2013 Show History China Labour Strikes (2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Beijing 20 Locations Beijing Chongqing Guangdong Shanghai Num Strikes 2 100 200 301 Year of Year 2014 Show History
- 7. China Labour Strikes(2011-2015) Guangdong Labour Strikes 2011-2015 Shanghai Labour Strikes 2011-2015 Labour Strikes Time Series 2011-2015 Labour Strikes Comparison 2011-2015 Labour Strikes Map 2011-2015 Guangdong 42 Chongqing 6 Shanghai 8 Beijing 5 Locations Beijing Chongqing Guangdong Shanghai Num Strikes 2 100 200 301 Year of Year 2015 Show History
- 8. 2. The screenshots of each year from the dynamic bubble graph using google Chart Tools are shown below:
- 11. Appendix 1. The datawere collected from January, 2011 to February, 2015 from China Labour Bulletin (http://maps.clb.org.hk/strikes/en). Data were recorded as monthly and saved in Excel spreadsheet format. Two data sets (labour.csv and labour.alt.csv) were then generated by R codes to created plots in Tableau. # Project 01 #install.packages("xlsx", dependencies=TRUE) #install.packages("lubridate", dependencies=TRUE) #install.packages("zoo") library(xlsx) library(lubridate) library(zoo) # 1a. strikes = read.xlsx("I:/STAT6610/Homework/project1/proj01_strikes.xlsx", sheetName="Labour", as.data.frame=TRUE,header=TRUE) # calculate strikes by year by locations # This is to make one plot with all four Locations on the time plot in different colors. # Also for dynamic bubble graph and stacked up bar graph. year=rep(c("2011/12/31","2012/12/31","2013/12/31","2014/12/31", "2015/02/28"),4) locations=rep(c("Beijing","Chongqing","Guangdong","Shanghai"),each=5) num_strikes=numeric(length(year)) for (i in 1:length(year)) { num_strikes[i]=sum(strikes$Strikes[which(year(strikes$Date)==year(year[i]) & (strikes$Locations==locations[i]))]) } labour=data.frame(year, locations, num_strikes) write.csv(labour, "I:/STAT6610/Homework/project1/labour.csv",row.names=FALSE ) # create another data set for individual bar graph and cluster bar graph Year=c("2011/12/31","2012/12/31","2013/12/31","2014/12/31", "2015/02/28") Beijing=num_strikes[1:5] Chongqing=num_strikes[6:10] Guangdong=num_strikes[11:15] Shanghai=num_strikes[16:20] labour.alt=data.frame(Year,Beijing,Chongqing,Guangdong,Shanghai) write.csv(labour.alt, "I:/STAT6610/Homework/project1/labour.alt.csv",row.names=FALSE)
- 12. labour.csv 2. R codeto produce the dynamic bubble graph using google Chart Tools. install.packages("googleVis") library(googleVis) labour=read.csv("I:/STAT6610/Homework/project1/labour.csv",header=TRUE,sep=",") # create another data set for dynamic bubble graph using google Chart Tools Year = year(labour$year) locations=labour$locations num_strikes=labour$num_strikes labour.g=data.frame(locations, Year, num_strikes) M1 <- gvisMotionChart(labour.g, idvar="locations", timevar="Year", sizevar="num_strikes") plot(M1)