simple notebook example

jupyter-xeus · Nov 20, 2023 · c1a710a · c1a710a
1 parent 5afb721
commit c1a710a
Showing 1 changed file with 157 additions and 5 deletions.
diff --git a/notebooks/xeus-r.ipynb b/notebooks/xeus-r.ipynb
@@ -13,29 +13,181 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Simple code execution"
+    "# Builtin data structures\n",
+    "\n",
+    "Vectors, lists, data frames "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# simple data structures\n",
+    "1:10\n",
+    "letters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# lists\n",
+    "list(a = 42, b = 1:5, c = sample(LETTERS, 10))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# data frames\n",
+    "head(mtcars)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# tibbles\n",
+    "suppressPackageStartupMessages({\n",
+    "    library(dplyr)\n",
+    "})\n",
+    "\n",
+    "mtcars %>%\n",
+    "  group_by(cyl) %>%\n",
+    "  summarise(mpg = mean(mpg))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "source": [
+    "At the moment, these automatically go through `display()` > `prepare_mimebundle()` > `repr()`, which offers several options in the mime bundle. I'm not sure this is the right approach, e.g. the automatic fancy display for simple data structures is somewhat overwhelming. I believe `display()` should be explicit. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "IRdisplay::prepare_mimebundle(1:10)\n",
+    "IRdisplay::prepare_mimebundle(list(a = 42, b = 1:5, c = sample(LETTERS, 10)))\n",
+    "IRdisplay::prepare_mimebundle(head(mtcars))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# plots"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# base graphics\n",
+    "boxplot(count ~ spray, data = InsectSprays, col = \"lightgray\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# ggplot2\n",
+    "options()\n",
+    "library(ggplot2)\n",
+    "\n",
+    "ggplot(mpg, aes(displ, hwy, colour = class)) + \n",
+    "  geom_point()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
+   "source": [
+    "# html widgets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "r"
+    }
+   },
    "outputs": [],
    "source": [
-    "a = 3"
+    "suppressPackageStartupMessages({\n",
+    "    library(htmltools)\n",
+    "    library(plotly)\n",
+    "})\n",
+    "\n",
+    "tagList(\n",
+    "  plot_ly(diamonds, x = ~carat, height = 200),\n",
+    "  plot_ly(diamonds, x = ~price, height = 200)\n",
+    ")"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 4.3.1 (xr)",
-   "language": "text/x-R",
+   "display_name": "R 4.3.1 (xr)",
+   "language": "R",
    "name": "xr"
   },
   "language_info": {
+   "codemirror_mode": "",
    "file_extension": "R",
    "mimetype": "text/x-R",
-   "name": "xr",
+   "name": "R",
+   "nbconvert_exporter": "",
+   "pygments_lexer": "",
    "version": "4.3.1"
   }
  },