{"id":2060,"date":"2019-11-05T23:19:44","date_gmt":"2019-11-05T14:19:44","guid":{"rendered":"http:\/\/141.164.34.82\/?p=2060"},"modified":"2019-11-05T23:22:33","modified_gmt":"2019-11-05T14:22:33","slug":"big-data-plots","status":"publish","type":"post","link":"http:\/\/ds.sumeun.org\/?p=2060","title":{"rendered":"Big data plots"},"content":{"rendered":"<h1>\ube45\ub370\uc774\ud130 \ud50c\ub86f<\/h1>\n<h2>\uc5b4\ub514\uc5d0 \uadf8\ub9b4 \uac83\uc778\uac00?<\/h2>\n<p>\uc708\ub3c4\uc6b0\uc5d0\uc11c <code>X11()<\/code> \ub610\ub294 <code>x11()<\/code>\uc740 <code>windows()<\/code>\uc640 \ub3d9\uc77c\ud55c \uc5ed\ud560\uc744 \ud55c\ub2e4. plot\uc744 \uc704\ud55c \uc0c8\ub85c\uc6b4 \ucc3d\uc744 \uc5f0\ub2e4.<\/p>\n<p><img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/x11.png\" alt=\"\"\/><\/p>\n<h2>R Studio Plots<\/h2>\n<p>R studio\ub97c \uc0ac\uc6a9\ud55c\ub2e4\uba74 \ud50c\ub86f\uc740 \uae30\ubcf8\uc801\uc73c\ub85c R studio\uc758 Plots\uc5d0 \ud45c\uc2dc\ub41c\ub2e4. <\/p>\n<p><img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/Rstudio_plots.png\" alt=\"\"\/><\/p>\n<p>\uc774\uc804\uc758 \ud50c\ub86f\uc744 \uc190\uc27d\uac8c \ucc3e\uc544 \ubcfc \uc218 \uc788\uc5b4\uc11c \ud3b8\ub9ac\ud558\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub2e4. \ud558\uc9c0\ub9cc \ub300\uc6a9\ub7c9\uc758 \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud558\ub824\uba74 <strong>\ub354\ub514\ub2e4!<\/strong><\/p>\n<h2>R Studio plots vs <code>x11<\/code><\/h2>\n<p>\ub2e4\uc74c\uc758 R Studio plots\uacfc <code>x11<\/code>\uc758 \uc18d\ub3c4\ub97c \ube44\uad50\ud558\uace0 \uc788\ub2e4. <\/p>\n<pre><code class=\"r\">library(microbenchmark) #install.packages(&#39;microbenchmark&#39;)\r\n\r\nmbm &lt;- microbenchmark(\r\n  &quot;x11_n=1000&quot; = {\r\n    N=1000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    x11()\r\n    plot(y~x)\r\n    dev.off()\r\n  },\r\n  &quot;RStudio_n=1000&quot; = {\r\n    N=1000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    plot(y~x)\r\n  },\r\n  &quot;x11_n=10000&quot; = {\r\n    N=10000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    x11()\r\n    plot(y~x)\r\n    dev.off()\r\n  },\r\n  &quot;RStudio_n=10000&quot; = {\r\n    N=10000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    plot(y~x)\r\n  },\r\n  &quot;x11_n=100000&quot; = {\r\n    N=100000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    x11()\r\n    plot(y~x)\r\n    dev.off()\r\n  },\r\n  &quot;RStudio_n=100000&quot; = {\r\n    N=100000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    plot(y~x)\r\n  },\r\n  &quot;x11_n=1000000&quot; = {\r\n    N=1000000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    x11()\r\n    plot(y~x)\r\n    dev.off()\r\n  },\r\n  &quot;RStudio_n=1000000&quot; = {\r\n    N=1000000\r\n    x = rnorm(N)\r\n    y = x + rnorm(N)\r\n    plot(y~x)\r\n  },\r\n  times=10)\r\n<\/code><\/pre>\n<pre><code class=\"r\">library(dplyr)\r\nlibrary(tidyr)\r\nlibrary(ggplot2)\r\n\r\nmbm %&gt;% mutate(expr=as.character(expr)) %&gt;% \r\n  separate(expr, sep=&quot;_&quot;, into=c(&#39;cond&#39;, &#39;N&#39;)) %&gt;%\r\n  mutate(N=gsub(&quot;n=&quot;, &quot;&quot;, N)) %&gt;%\r\n  #filter(N %in% c(&#39;1000&#39;,&#39;10000&#39;,&#39;100000&#39;)) %&gt;%\r\n  ggplot(aes(x=N, col=cond, y=time\/1000)) +\r\n    geom_boxplot() + \r\n    coord_trans(y=&#39;log10&#39;) +\r\n    labs(y=&#39;time (sec)&#39;) -&gt; ggp\r\nprint(ggp)\r\n<\/code><\/pre>\n<p><img src=\"data:image\/png;base64,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\" alt=\"plot of chunk unnamed-chunk-3\"\/><\/p>\n<pre><code class=\"r\">#autoplot(mbm)\r\n<\/code><\/pre>\n<p>\uc774\uc720\ub294 \ubaa8\ub974\uaca0\uc9c0\ub9cc \ub370\uc774\ud130\uac00 \ucee4\uc9c8 \uc218\ub85d RStudio\uc758 Plots\ub294 <code>x11<\/code>\uc744 \ud1b5\ud574 \uc0c8\ub85c\uc6b4 \ucc3d\uc5d0 \uadf8\ub798\ud504\ub97c \uadf8\ub9ac\ub294 \uac83 \ubcf4\ub2e4 \ub290\ub9ac\ub2e4. (100\ub9cc\uac1c\uc758 \uc810\uc744 \uadf8\ub9ac\ub294\ub370 <code>x11<\/code>\uc758 \ud3c9\uade0\uc740 \uc57d 30\ucd08, R Studio\uc758 \uacbd\uc6b0\ub294 \ud3c9\uade0 \uc57d 40\ucd08\uac00 \uac78\ub838\ub2e4.)<\/p>\n<p>\uc0ac\uc2e4 \uc2ed\ub9cc\uac1c\ub97c \ub118\uc5b4\uac00 \ubc31\ub9cc\uac1c\uc758 \uc810\uc744 \uadf8\ub798\ud504\ub85c \uadf8\ub9ac\ub294 \uac83\uc740 \uc870\uae08 \uc624\ubc84\ub77c\uace0 \uc0dd\uac01\ud55c\ub2e4. \uc5bc\ub9c8\ub098 \ud070 \uc885\uc774\uc5d0 \uadf8\ub9ac\ub290\ub0d0\uc5d0 \ub530\ub77c \ub2e4\ub974\uaca0\uc9c0\ub9cc, \ub300\ubd80\ubd84\uc758 \uc810\ub4e4\uc740 \uc11c\ub85c \uacb9\uccd0\uc11c \uad6c\ubd84\uc774 \ubd88\uac00\ud558\uae30 \ub54c\ubb38\uc774\ub2e4.<\/p>\n<pre><code class=\"r\">require(scales)\r\n\r\nN=100000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=1))\r\n\r\nN=100000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=0.1))\r\n\r\nN=100000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=0.01))\r\n\r\nN=1000000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=1))\r\n\r\nN=1000000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=0.1))\r\n\r\nN=1000000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=0.01))\r\n\r\nN=1000000\r\nx = rnorm(N)\r\ny = x + rnorm(N)\r\nplot(y~x, col=alpha(&#39;black&#39;, alpha=0.001))\r\n<\/code><\/pre>\n<p><img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n100000_a1.png\" alt=\"\"\/><br \/>\n<img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n100000_a01.png\" alt=\"\"\/><br \/>\n<img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n100000_a001.png\" alt=\"\"\/><\/p>\n<p><img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n1000000_a1.png\" alt=\"\"\/><br \/>\n<img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n1000000_a01.png\" alt=\"\"\/><br \/>\n<img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n1000000_a001.png\" alt=\"\"\/><br \/>\n<img src=\"http:\/\/141.164.34.82\/wp-content\/uploads\/2019\/11\/n1000000_a0001.png\" alt=\"\"\/><\/p>\n<p><code>alpha=0.001<\/code>\uc740 \uc791\ub3d9\ud558\uc9c0 \uc54a\ub294 \ub4ef \ud558\ub2e4.<\/p>\n<h2>\uacb0\ub860<\/h2>\n<p>\uc801\uc5b4\ub3c4 \ub2e4\uc74c\uc758 \uc138\ud305\uc5d0\uc11c \ud50c\ub86f\ud574\uc57c \ud560 \ub370\uc774\ud130\uac00 \uc99d\uac00\ud568\uc5d0 \ub530\ub77c R Studio\uc758 Viewer\ub85c \ud50c\ub86f\ud558\ub294 \uac83\uc740 \uc0c8\ub85c\uc6b4 \uc708\ub3c4\uc6b0\ub97c \uc5f4\uc5b4\uc11c \ud50c\ub86f\ud558\ub294 \uac83\ubcf4\ub2e4 \ub290\ub9ac\ub2e4.<\/p>\n<pre><code class=\"r\"># install.packges(&#39;rstudioapi&#39;)\r\nver &lt;- rstudioapi::versionInfo()\r\nver\r\nsessionInfo()\r\n<\/code><\/pre>\n<pre>## $citation\r\n## \r\n## To cite RStudio in publications use:\r\n## \r\n##   RStudio Team (2018). RStudio: Integrated Development for R.\r\n##   RStudio, Inc., Boston, MA URL http:\/\/www.rstudio.com\/.\r\n## \r\n## A BibTeX entry for LaTeX users is\r\n## \r\n##   @Manual{,\r\n##     title = {RStudio: Integrated Development Environment for R},\r\n##     author = {{RStudio Team}},\r\n##     organization = {RStudio, Inc.},\r\n##     address = {Boston, MA},\r\n##     year = {2018},\r\n##     url = {http:\/\/www.rstudio.com\/},\r\n##   }\r\n## \r\n## \r\n## $mode\r\n## [1] &quot;desktop&quot;\r\n## \r\n## $version\r\n## [1] &#39;1.2.1335&#39;\r\n<\/pre>\n<pre>## R version 3.6.1 (2019-07-05)\r\n## Platform: x86_64-w64-mingw32\/x64 (64-bit)\r\n## Running under: Windows 10 x64 (build 18362)\r\n## \r\n## Matrix products: default\r\n## \r\n## locale:\r\n## [1] LC_COLLATE=Korean_Korea.949  LC_CTYPE=Korean_Korea.949   \r\n## [3] LC_MONETARY=Korean_Korea.949 LC_NUMERIC=C                \r\n## [5] LC_TIME=Korean_Korea.949    \r\n## \r\n## attached base packages:\r\n## [1] stats     graphics  grDevices utils     datasets  methods   base     \r\n## \r\n## other attached packages:\r\n##  [1] XMLRPC_0.3-1         knitr_1.25           RWordPress_0.2-3    \r\n##  [4] data.table_1.12.6    stringr_1.4.0        tidyr_1.0.0         \r\n##  [7] microbenchmark_1.4-7 ggplot2_3.2.1        dplyr_0.8.3         \r\n## [10] mclust_5.4.5         mvtnorm_1.0-11       flexmix_2.3-15      \r\n## [13] lattice_0.20-38     \r\n## \r\n## loaded via a namespace (and not attached):\r\n##  [1] Rcpp_1.0.2        highr_0.8         pillar_1.4.2     \r\n##  [4] compiler_3.6.1    bitops_1.0-6      tools_3.6.1      \r\n##  [7] zeallot_0.1.0     digest_0.6.22     lifecycle_0.1.0  \r\n## [10] evaluate_0.14     tibble_2.1.3      gtable_0.3.0     \r\n## [13] pkgconfig_2.0.3   rlang_0.4.1       rstudioapi_0.10  \r\n## [16] yaml_2.2.0        xfun_0.10         withr_2.1.2      \r\n## [19] vctrs_0.2.0       stats4_3.6.1      grid_3.6.1       \r\n## [22] nnet_7.3-12       tidyselect_0.2.5  glue_1.3.1       \r\n## [25] R6_2.4.0          XML_3.98-1.20     rmarkdown_1.16   \r\n## [28] purrr_0.3.3       magrittr_1.5      ellipsis_0.3.0   \r\n## [31] backports_1.1.5   scales_1.0.0      modeltools_0.2-22\r\n## [34] htmltools_0.4.0   assertthat_0.2.1  mime_0.7         \r\n## [37] colorspace_1.4-1  labeling_0.3      stringi_1.4.3    \r\n## [40] RCurl_1.95-4.12   lazyeval_0.2.2    munsell_0.5.0    \r\n## [43] markdown_1.1      crayon_1.3.4\r\n<\/pre>\n<ul>\n<li>PS: \uacbd\ud5d8 \uc0c1 Python\uc740 R\ubcf4\ub2e4 \ube68\ub790\ub2e4. \uc544\ub9c8\ub3c4 \ud50c\ub86f\uc5d0 \uac1c\uac1c\uc758 \ub370\uc774\ud130 \uc815\ubcf4\uac00 \uc800\uc7a5\ub418\ub294 \ubc29\uc2dd\uc774 \uc544\ub2c8\ub77c \uadf8\ub9bc\uc73c\ub85c \ucd9c\ub825\ub418\uace0 \ub05d\ub098\uae30 \ub54c\ubb38\uc778 \ub4ef\ud558\ub2e4.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>\ube45\ub370\uc774\ud130 \ud50c\ub86f \uc5b4\ub514\uc5d0 \uadf8\ub9b4 \uac83\uc778\uac00? \uc708\ub3c4\uc6b0\uc5d0\uc11c X11() \ub610\ub294 x11()\uc740 windows()\uc640 \ub3d9\uc77c\ud55c \uc5ed\ud560\uc744 \ud55c\ub2e4. plot\uc744 \uc704\ud55c \uc0c8\ub85c\uc6b4 \ucc3d\uc744 \uc5f0\ub2e4. R Studio Plots R studio\ub97c \uc0ac\uc6a9\ud55c\ub2e4\uba74 \ud50c\ub86f\uc740 \uae30\ubcf8\uc801\uc73c\ub85c R studio\uc758 Plots\uc5d0 \ud45c\uc2dc\ub41c\ub2e4. \uc774\uc804\uc758 \ud50c\ub86f\uc744 \uc190\uc27d\uac8c \ucc3e\uc544 \ubcfc \uc218 \uc788\uc5b4\uc11c \ud3b8\ub9ac\ud558\uac8c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub2e4. \ud558\uc9c0\ub9cc \ub300\uc6a9\ub7c9\uc758 \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud558\ub824\uba74 \ub354\ub514\ub2e4! R Studio plots vs x11 \ub2e4\uc74c\uc758 R Studio plots\uacfc [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2051,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[371,28,165],"tags":[415,414,416],"jetpack_featured_media_url":"http:\/\/ds.sumeun.org\/wp-content\/uploads\/2019\/11\/n1000000_a001.png","_links":{"self":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2060"}],"collection":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2060"}],"version-history":[{"count":2,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2060\/revisions"}],"predecessor-version":[{"id":2062,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/2060\/revisions\/2062"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/media\/2051"}],"wp:attachment":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2060"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2060"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2060"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}