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    <p><strong>Edit:</strong> Response to OP's comment. </p> <p>This directly creates a line chart of OP's data. Below this is the original answer using <code>ggplot</code>, which produces a far superior output.</p> <p>Given the frequency table you provided,</p> <pre><code>df &lt;- data.frame(t(freqTable)) # transpose (more suitable for plotting) df &lt;- cbind(Response=rownames(df),df) # add row names as first column plot(as.numeric(df$Response),df$f,type="b",col="red", xaxt="n", ylab="Count",xlab="Response") lines(as.numeric(df$Response),df$m,type="b",col="blue") axis(1,at=c(1,2,3,4,5,6),labels=c("Str.Agr.","Sl.Agr","Neither","Sl.Disagr","Str.Disagr","NA")) </code></pre> <p>Produces this, which seems like what you were looking for. <img src="https://i.stack.imgur.com/rbZ5h.png" alt=""></p> <p><strong>Original Answer:</strong></p> <p>Not quite what you asked for, but converting your frequency table to a data frame, <code>df</code></p> <pre><code>df &lt;- data.frame(freqTable) df &lt;- cbind(Gender=rownames(df),df) # append rownames (Gender) df &lt;- df[-3,] # drop unknown gender df # Gender X1 X2 X3 X4 X5 X8 # m m 5 16 3 16 5 0 # f f 12 25 3 10 3 1 df &lt;- df[-3,] # remove unknown gender column library(ggplot2) library(reshape2) gg=melt(df) labels &lt;- c("Agree\nFully","Somewhat\nAgree","Neither Agree\nnor Disagree","Somewhat\nDisagree","Disagree\nFully", "No Answer") ggp &lt;- ggplot(gg,aes(x=variable,y=value)) ggp &lt;- ggp + geom_bar(aes(fill=Gender), position="dodge", stat="identity") ggp &lt;- ggp + scale_x_discrete(labels=labels) ggp &lt;- ggp + theme(axis.text.x = element_text(angle=90, vjust=0.5)) ggp &lt;- ggp + labs(x="", y="Frequency") ggp </code></pre> <p>Produces this: <img src="https://i.stack.imgur.com/70kNs.png" alt=""></p> <p>Or, this, which is much better:</p> <pre><code>ggp + facet_grid(Gender~.) </code></pre> <p><img src="https://i.stack.imgur.com/mrKuf.png" alt=""></p>
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    1. COWell, I appreciate your suggestions. Of course, with the ggplot package you could build much prettier graphs than with the normal plot function. But honestly, that doesn't solve my problem. :/ I was just wondering what would be the best way to build a line chart with my given dataset. Also @Frank mentioned that bar chart would be more appropriate for the given data, and I know that. But again, please consider the data just as an example.
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