r - ggplot 2 "Error: Discrete value supplied to continuous scale" -


i ask how fix bug described in question title? yesterday, code working fine , plotting routine produced desired graph. woke today , tried add features , got error message.

any clue why , how fix this?

thx

data link: data.csv

code:

    # loading data     morstats <- read.csv(file = "f:/purdue university/ra_position/phd_researchanddissert/phd_draft/dissertationdraft/moroccocge-cc_stats.csv", header=true, sep=",", na.string="na", dec=".", strip.white=true)      # transferring .csv data data frames     moroccostats <- as.data.frame(morstats)      # changing data in dataframe "as.numeric"     moroccostats[3:38] <- sapply(moroccostats[3:38],as.numeric)     moroccostats <- droplevels(moroccostats)      # reorder      moroccostats <- transform(moroccostats,year=factor(year,levels=unique(year)))      # load packages     library(reshape2)     library(ggplot2)     library(lattice)     library(grid)     library(plyr)     library(gridextra)     library(scales)      #----------------------------------------------------------------------     # figure 1: evolution of population (in absolute terms) 1960-2050     #---------------------------------------------------------------------      #_code_begin...      moroccostats.f <- melt(moroccostats, id="year")     morstats.pop <- moroccostats.f[moroccostats.f$variable %in% c("pop_t","pop_ur","pop_ru"),]      figure1 <- ggplot(data=morstats.pop,aes(x=factor(year), y=value,colour=variable))     figure1 + geom_line(aes(group=factor(variable)),size=1) + geom_point() + scale_colour_manual("population",labels=c("total","urban","rural"),values = c("black","red","blue")) +     labs(y="population (in 1000)") +      theme(axis.text.x = element_text(colour = 'black', angle = 90, size = 13, hjust = 1, vjust = 0.5),axis.title.x = element_blank()) +      theme(axis.text.y = element_text(colour = 'black', size = 13, hjust = 0.5, vjust = 0.5), axis.title.y = element_text(size = 10, hjust = 0.5, vjust = 0.2, face = 'bold')) +     scale_x_discrete(breaks = seq(1960, 2050, by=2)) +     scale_y_continuous(breaks = seq(0, 42000, by=5000))      #_code_end...

moroccostats has structure

> str(moroccostats) 'data.frame':   91 obs. of  38 variables:  $ year            : factor w/ 91 levels "1960","1961",..: 1 2 3 4 5 6 7 8 9 10 ...  $ periodframe     : factor w/ 4 levels "0","phase 1 (1965 1985)",..: 1 1 1 1 1 2 2 2 2 2 ...  $ pop_t           : num  11635 11897 12177 12473 12785 ...  $ pop_ur          : num  3395 3547 3703 3862 4026 ...  ...

when melt year moroccostats.f, get

> str(moroccostats.f) 'data.frame':   3367 obs. of  3 variables:  $ year    : factor w/ 91 levels "1960","1961",..: 1 2 3 4 5 6 7 8 9 10 ...  $ variable: factor w/ 37 levels "periodframe",..: 1 1 1 1 1 1 1 1 1 1 ...  $ value   : chr  "0" "0" "0" "0" ...

note value character because periodframe factor. i'm guessing changed periodframe went being number character (the "phase 1 (1965 1985)" bits).

since plotting pop_t , pop_ur , pop_ru columns, pull out before melting

morstats.pop <- melt(moroccostats[c("year","pop_t","pop_ur","pop_ru")], id="year")

then don't have worry coercions other types dues irrelevant columns.


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