<\/path><\/svg><\/span>import<\/span> matplotlib.pyplot <\/span>as<\/span> plt <\/span><\/span>\n<\/span>\nyears = [<\/span>2011<\/span>, <\/span>2012<\/span>, <\/span>2013<\/span>, <\/span>2014<\/span>, <\/span>2015<\/span>, <\/span>2016<\/span>, <\/span>2017<\/span>, <\/span>2018<\/span>, <\/span>2019<\/span>, <\/span>2020<\/span>, <\/span>2021<\/span>, <\/span>2022<\/span>, <\/span>2023<\/span>]<\/span><\/span>\npopulation = [<\/span>0.77<\/span>,\t<\/span>0.53<\/span>,\t<\/span>0.46<\/span>,\t<\/span>0.63<\/span>,\t<\/span>0.53<\/span>,\t<\/span>0.40<\/span>,\t<\/span>0.28<\/span>,\t<\/span>0.43<\/span>,\t<\/span>0.35<\/span>,\t<\/span>0.14<\/span>,\t-<\/span>0.18<\/span>,\t-<\/span>0.23<\/span>,\t-<\/span>0.14<\/span>]<\/span><\/span>\n <\/span><\/span>\nplt.plot(years, population, <\/span>color<\/span>=<\/span>"b"<\/span>, <\/span>marker<\/span>=<\/span>"o"<\/span>, <\/span>linestyle<\/span>=<\/span>"--"<\/span>)<\/span><\/span>\n <\/span><\/span>\nplt.title(<\/span>'Population increase in South Korea'<\/span>) <\/span><\/span>\n <\/span><\/span>\nplt.ylabel(<\/span>'unit %'<\/span>)<\/span><\/span>\nplt.savefig(<\/span>'population_graph.png'<\/span>, <\/span>dpi<\/span> = <\/span>600<\/span>)<\/span><\/span>\nplt.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<\/p>\n\n\n\n
\uc704\uc5d0 \ucf54\ub4dc\ub97c \uc2e4\ud589\ud558\uc2dc\uba74 \uc544\ub798\uc640 \uac19\uc740 \uadf8\ub798\ud504\ub97c \uc5bb\uc744 \uc218 \uc788\ub294\ub370\uc694. <\/p>\n\n\n\n
\uacb0\uacfc<\/strong>:<\/p>\n\n\n\n