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I was getting ready for school and about to wear my uniform when I remembered that our principal had told us not to wear uniforms. So I decided to wear my favorite pink dress (Malala Yousafzai)
After reading the diary of a Pakistani schoolgirl and Malala’s history, there is no doubt of being in front of a brave girl. A girl that will fight against monsters who deprive children of their childhood. A girl who knows that one book, one pen, one child and one teacher can change this unfair world. A girl who knew she had won the Nobel Prize of Peace in her chemistry lesson and finished the school time before making her first statement. A girl for whom the prize is just the beginning: a girl that gives us hope. Long live Malala:
To know where to obtain data for this plot, check out this post. This is the code:
require("sqldf") require("plyr") require("stringdist") childlabour=read.csv("UNdata_Export_20141013_ChildLabour.csv", nrows=335, header=T, row.names=NULL) education=read.csv("UNdata_Export_20141013_Education.csv", nrows=2994, header=T, row.names=NULL) population =read.csv("UNdata_Export_20140930_Population.csv", nrows=12846, header=T, row.names=NULL) population=rename(population, replace = c("Country.or.Area" = "Country")) education=rename(education, replace = c("Reference.Area" = "Country")) education=rename(education, replace = c("Time.Period" = "Year")) childlabour=rename(childlabour, replace = c("Country.or.Area" = "Country")) population=sqldf("SELECT a.Country, a.Year, a.Value as Pop FROM population a INNER JOIN (SELECT Country, MAX(Year) AS Year FROM population GROUP BY 1) b ON (a.Country=b.Country AND a.Year=b.Year) WHERE (a.Country NOT LIKE '%INCOME%') AND (a.Country NOT LIKE '%WORLD%') AND (a.Country NOT LIKE '%developing%') AND (a.Country NOT LIKE '%OECD%') AND (a.Country NOT LIKE '%countries%') AND (a.Country NOT LIKE '%South Asia%') AND (a.Country NOT LIKE '%Small states%') AND (a.Country NOT LIKE '%Euro area%') AND (a.Country NOT LIKE '%European Union%') AND (a.Country NOT LIKE '%North America%')") childlabour=sqldf("SELECT * FROM childlabour WHERE Subgroup='Total 5-14 yr'") education=sqldf("SELECT a.* FROM education a INNER JOIN (SELECT Country, MAX(Year) AS Year FROM education GROUP BY 1) b ON (a.Country=b.Country AND a.Year=b.Year)") data=sqldf("SELECT a.Country, a.Pop, b.Value as ChildLabour, c.Observation_Value as Education FROM population a INNER JOIN childlabour b ON (a.Country=b.Country) INNER JOIN education c ON (a.Country=c.Country)") require(ggplot2) require(scales) opts=theme( panel.background = element_rect(fill="gray98"), panel.border = element_rect(colour="black", fill=NA), axis.line = element_line(size = 0.5, colour = "black"), axis.ticks = element_line(colour="black"), panel.grid.major = element_line(colour="gray75", linetype = 2), panel.grid.minor = element_blank(), axis.text.y = element_text(colour="gray25", size=15), axis.text.x = element_text(colour="gray25", size=15), text = element_text(size=20), legend.key = element_blank(), legend.position = "none", legend.background = element_blank(), plot.title = element_text(size = 45) ) ggplot(data, aes(x=ChildLabour/100, y=Education/100, size=log(Pop), label=Country), guide=FALSE)+ geom_point(colour="white", fill="red", shape=21, alpha=.55)+ scale_size_continuous(range=c(2,40))+ scale_x_continuous(limits=c(0,.5), labels = percent)+ scale_y_continuous(limits=c(0,.12), labels = percent)+ labs(title="The World We Live In #2: To Study Or To Work", x="% of Child Workers between 5-14 years old", y="Public Expenditure on Education as % of GNI")+ geom_text(data=subset(data, ChildLabour/100>.3 | Education/100>.07| Education/10<.022), size=5.5, colour="gray25", hjust=0, vjust=0)+ geom_text(aes(.2, .0), colour="gray25", hjust=0, label="Countries of the world (Source: United Nations Statistics Division) Size of bubble depending on population", size=5)+ opts
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