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yssymmt/boxplot_ggplot2.ipynb

Created August 12, 2023 13:48
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boxplot_ggplot2.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "b3062072-d8fa-47bf-aecd-1f7ea52c93be",
"metadata": {},
"source": [
"### 箱ひげ図を描いてみよう ggplot2編"
]
},
{
"cell_type": "markdown",
"id": "542e7401-9557-4c94-887b-64662f84c2e0",
"metadata": {},
"source": [
"#### ライブラリの読み込み"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d4b1b1d1-d666-48d9-ab22-b5f385041728",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"── \u001b[1mAttaching core tidyverse packages\u001b[22m ───────────────────────────────────────────────────────── tidyverse 2.0.0 ──\n",
"\u001b[32m✔\u001b[39m \u001b[34mdplyr \u001b[39m 1.1.0 \u001b[32m✔\u001b[39m \u001b[34mreadr \u001b[39m 2.1.4\n",
"\u001b[32m✔\u001b[39m \u001b[34mforcats \u001b[39m 1.0.0 \u001b[32m✔\u001b[39m \u001b[34mstringr \u001b[39m 1.5.0\n",
"\u001b[32m✔\u001b[39m \u001b[34mggplot2 \u001b[39m 3.4.1 \u001b[32m✔\u001b[39m \u001b[34mtibble \u001b[39m 3.1.8\n",
"\u001b[32m✔\u001b[39m \u001b[34mlubridate\u001b[39m 1.9.2 \u001b[32m✔\u001b[39m \u001b[34mtidyr \u001b[39m 1.3.0\n",
"\u001b[32m✔\u001b[39m \u001b[34mpurrr \u001b[39m 1.0.1 \n",
"── \u001b[1mConflicts\u001b[22m ─────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m masks \u001b[34mstats\u001b[39m::lag()\n",
"\u001b[36mℹ\u001b[39m Use the conflicted package (\u001b[3m\u001b[34m<http://conflicted.r-lib.org/>\u001b[39m\u001b[23m) to force all conflicts to become errors\n"
]
}
],
"source": [
"library(tidyverse)\n",
"#library(dplyr)\n",
"#library(ggplot2)"
]
},
{
"cell_type": "markdown",
"id": "1ad7b5c3-bb1c-4f1a-bbd8-053880d5ce96",
"metadata": {},
"source": [
"#### ファイルの読み込み"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "035b97b7-f049-4681-89c8-45f65b608f6e",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[1mRows: \u001b[22m\u001b[34m9\u001b[39m \u001b[1mColumns: \u001b[22m\u001b[34m8\u001b[39m\n",
"\u001b[36m──\u001b[39m \u001b[1mColumn specification\u001b[22m \u001b[36m─────────────────────────────────────────────────────────────────────────────────────────\u001b[39m\n",
"\u001b[1mDelimiter:\u001b[22m \",\"\n",
"\u001b[31mchr\u001b[39m (2): 色, 変数名\n",
"\u001b[32mdbl\u001b[39m (6): 最小値, 第1四分位, 第2四分位, 第3四分位, 最大値, 平均値\n",
"\n",
"\u001b[36mℹ\u001b[39m Use `spec()` to retrieve the full column specification for this data.\n",
"\u001b[36mℹ\u001b[39m Specify the column types or set `show_col_types = FALSE` to quiet this message.\n"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A tibble: 6 × 8</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>色</th><th scope=col>変数名</th><th scope=col>最小値</th><th scope=col>第1四分位</th><th scope=col>第2四分位</th><th scope=col>第3四分位</th><th scope=col>最大値</th><th scope=col>平均値</th></tr>\n",
"\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>a</td><td>変数1</td><td>4</td><td> 6</td><td>19</td><td>20</td><td>33</td><td>16.6</td></tr>\n",
"\t<tr><td>b</td><td>変数2</td><td>4</td><td> 7</td><td>17</td><td>25</td><td>29</td><td>16.8</td></tr>\n",
"\t<tr><td>a</td><td>変数3</td><td>3</td><td>10</td><td>12</td><td>24</td><td>28</td><td>15.8</td></tr>\n",
"\t<tr><td>b</td><td>変数4</td><td>3</td><td> 6</td><td>16</td><td>26</td><td>28</td><td>16.2</td></tr>\n",
"\t<tr><td>a</td><td>変数5</td><td>1</td><td> 6</td><td>15</td><td>23</td><td>29</td><td>15.4</td></tr>\n",
"\t<tr><td>b</td><td>変数6</td><td>5</td><td>10</td><td>16</td><td>22</td><td>30</td><td>17.4</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A tibble: 6 × 8\n",
"\\begin{tabular}{llllllll}\n",
" 色 & 変数名 & 最小値 & 第1四分位 & 第2四分位 & 第3四分位 & 最大値 & 平均値\\\\\n",
" <chr> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\t a & 変数1 & 4 & 6 & 19 & 20 & 33 & 16.6\\\\\n",
"\t b & 変数2 & 4 & 7 & 17 & 25 & 29 & 16.8\\\\\n",
"\t a & 変数3 & 3 & 10 & 12 & 24 & 28 & 15.8\\\\\n",
"\t b & 変数4 & 3 & 6 & 16 & 26 & 28 & 16.2\\\\\n",
"\t a & 変数5 & 1 & 6 & 15 & 23 & 29 & 15.4\\\\\n",
"\t b & 変数6 & 5 & 10 & 16 & 22 & 30 & 17.4\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A tibble: 6 × 8\n",
"\n",
"| 色 &lt;chr&gt; | 変数名 &lt;chr&gt; | 最小値 &lt;dbl&gt; | 第1四分位 &lt;dbl&gt; | 第2四分位 &lt;dbl&gt; | 第3四分位 &lt;dbl&gt; | 最大値 &lt;dbl&gt; | 平均値 &lt;dbl&gt; |\n",
"|---|---|---|---|---|---|---|---|\n",
"| a | 変数1 | 4 | 6 | 19 | 20 | 33 | 16.6 |\n",
"| b | 変数2 | 4 | 7 | 17 | 25 | 29 | 16.8 |\n",
"| a | 変数3 | 3 | 10 | 12 | 24 | 28 | 15.8 |\n",
"| b | 変数4 | 3 | 6 | 16 | 26 | 28 | 16.2 |\n",
"| a | 変数5 | 1 | 6 | 15 | 23 | 29 | 15.4 |\n",
"| b | 変数6 | 5 | 10 | 16 | 22 | 30 | 17.4 |\n",
"\n"
],
"text/plain": [
" 色 変数名 最小値 第1四分位 第2四分位 第3四分位 最大値 平均値\n",
"1 a 変数1 4 6 19 20 33 16.6 \n",
"2 b 変数2 4 7 17 25 29 16.8 \n",
"3 a 変数3 3 10 12 24 28 15.8 \n",
"4 b 変数4 3 6 16 26 28 16.2 \n",
"5 a 変数5 1 6 15 23 29 15.4 \n",
"6 b 変数6 5 10 16 22 30 17.4 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dat <- read_csv(\"boxplot_dat.csv\")\n",
"head(dat)"
]
},
{
"cell_type": "markdown",
"id": "cb40b05e-2d2e-481b-b16d-e4899255098b",
"metadata": {},
"source": [
"#### 利用フォントの指定"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "7ebbab28-cb6b-4705-9275-637ae7378e68",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"windowsFonts(Meiryo = windowsFont(\"Meiryo\"))"
]
},
{
"cell_type": "markdown",
"id": "8078d0db-ddab-4289-a342-429d478df53a",
"metadata": {},
"source": [
"#### 横に表示する"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "32b3d3d6-b40a-4e89-a959-2e53dbc68bf1",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"viz01 <- ggplot(dat, aes(\n",
" x = 変数名, \n",
" ymin = 最小値, \n",
" lower = 第1四分位, \n",
" middle = 第2四分位, \n",
" upper = 第3四分位, \n",
" ymax = 最大値, \n",
" y = 平均値 \n",
")) + \n",
"theme_minimal(base_family = \"Meiryo\") + \n",
"theme ( \n",
" axis.text.x = element_text(size = 5), \n",
" axis.text.y = element_text(size = 5), \n",
" axis.title.x = element_text(size = 5), \n",
" axis.title.y = element_text(size = 5)\n",
") + \n",
"labs(\n",
" y=\"中央値が線、平均値が赤点\"\n",
") + \n",
"geom_boxplot(stat = \"identity\", linewidth=0.25, alpha=0.5, fill=\"#00A4A0\", colour=\"#A6A6A6\") + \n",
"geom_point(shape=20, size=1, colour=\"red\", alpha=0.5)"
]
},
{
"cell_type": "markdown",
"id": "d16d2ff9-e141-49b7-914c-d74158889dbe",
"metadata": {},
"source": [
"#### 画像ファイルの作成"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "af9d516f-3412-4532-b481-fa074195ed08",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ggsave(\"viz01.png\", viz01, dpi=500, width=5, height=2.5, bg=\"#ffffff\")"
]
},
{
"cell_type": "markdown",
"id": "a84ecccf-c73f-4412-a06f-bbe9ff85337e",
"metadata": {},
"source": [
"###### 以下のセルをマークダウンにして画像ファイルをドラッグ"
]
},
{
"attachments": {
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}
},
"cell_type": "markdown",
"id": "03407514-6f2f-48dd-857a-2a8abb666b7b",
"metadata": {},
"source": [
"![viz01.png](attachment:dd2e9b54-74ff-4cdb-b1d3-83ea879a8620.png)"
]
},
{
"cell_type": "markdown",
"id": "66b6ca12-70f8-424e-9c2b-c0a94750fe08",
"metadata": {},
"source": [
"#### 縦に表示する"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "5371fb78-0735-46a9-b01d-211441377aa9",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"viz02 <- ggplot(dat, aes(\n",
" y = 変数名, \n",
" xmin = 最小値, \n",
" xlower = 第1四分位, \n",
" xmiddle = 第2四分位, \n",
" xupper = 第3四分位, \n",
" xmax = 最大値, \n",
" x = 平均値 \n",
")) + \n",
"theme_minimal(base_family = \"Meiryo\") + \n",
"theme ( \n",
" axis.text.x = element_text(size = 5), \n",
" axis.text.y = element_text(size = 5), \n",
" axis.title.x = element_text(size = 5), \n",
" axis.title.y = element_text(size = 5)\n",
") + \n",
"labs(\n",
" x=\"中央値が線、平均値が赤点\"\n",
") + \n",
"geom_boxplot(stat = \"identity\", linewidth=0.25, alpha=0.5, fill=\"#00A4A0\", colour=\"#A6A6A6\") + \n",
"geom_point(shape=20, size=1, colour=\"red\", alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "cb138fe7-fe05-43e0-a074-59e4bacb42a5",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ggsave(\"viz02.png\", viz02, dpi=500, width=5, height=2.5, bg=\"#ffffff\")"
]
},
{
"attachments": {
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"image/png": 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}
},
"cell_type": "markdown",
"id": "394f0624-fa5e-4c21-a674-a6d72ceadccb",
"metadata": {},
"source": [
"![viz02.png](attachment:99272952-c43f-466e-8752-5a374d61ee32.png)"
]
},
{
"cell_type": "markdown",
"id": "71deb734-6a7c-4e02-8c3e-fc49fabfbd96",
"metadata": {},
"source": [
"#### 色分けする"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "81221b83-57a6-4df7-b265-2ca149640de7",
"metadata": {},
"outputs": [],
"source": [
"viz03 <- ggplot(dat, aes(\n",
" x = 変数名, \n",
" ymin = 最小値, \n",
" lower = 第1四分位, \n",
" middle = 第2四分位, \n",
" upper = 第3四分位, \n",
" ymax = 最大値, \n",
" y = 平均値, \n",
" fill = 色 \n",
")) + \n",
"theme_minimal(base_family = \"Meiryo\") + \n",
"theme ( \n",
" axis.text.x = element_text(size = 5), \n",
" axis.text.y = element_text(size = 5), \n",
" axis.title.x = element_text(size = 5), \n",
" axis.title.y = element_text(size = 5), \n",
" legend.position = \"none\" #凡例の非表示\n",
") + \n",
"labs(\n",
" y=\"中央値が線、平均値が赤点\"\n",
") + \n",
"geom_boxplot(stat = \"identity\", linewidth=0.25, alpha=0.5, colour=\"#A6A6A6\") + \n",
"scale_fill_manual(values = c(\"#FF6161\",\"#EB6E19\")) + \n",
"geom_point(shape=20, size=1, colour=\"red\", alpha=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "979b74d9-139d-4fdf-9b08-76a5553746e1",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"ggsave(\"viz03.png\", viz03, dpi=500, width=5, height=2.5, bg=\"#ffffff\")"
]
},
{
"attachments": {
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"image/png": 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}
},
"cell_type": "markdown",
"id": "121a21fb-6cc1-4d28-b94b-7e9a44ed55b9",
"metadata": {},
"source": [
"![viz03.png](attachment:b4b5256b-8dfe-474b-9e7b-24ac67a2e11a.png)"
]
},
{
"cell_type": "markdown",
"id": "ea26d9be-92cc-437d-9d5e-30c3e2ae7bd5",
"metadata": {},
"source": [
"#### 参照 "
]
},
{
"cell_type": "markdown",
"id": "350cb19d-390d-4536-85a5-d31a56977b49",
"metadata": {},
"source": [
"https://statisticsglobe.com/draw-boxplot-precomputed-values-r <br>\n",
"https://ggplot2.tidyverse.org/reference/geom_boxplot.html <br>"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "4.2.2"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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