2021 december edition - update materials (#149)

Author: jorisvandenbossche

_solved/00-jupyter_introduction.ipynb

@@ -6,9 +6,6 @@
    "source": [
     "<p><font size=\"6\"><b> CASE - air quality data of European monitoring stations (AirBase)</b></font></p>\n",
     "\n",
-    "> *DS Data manipulation, analysis and visualization in Python*  \n",
-    "> *May/June, 2021*\n",
-    ">\n",
     "> *© 2021, Joris Van den Bossche and Stijn Van Hoey  (<mailto:[email protected]>, <mailto:[email protected]>). Licensed under [CC BY 4.0 Creative Commons](http://creativecommons.org/licenses/by/4.0/)*\n",
     "\n",
     "---"
@@ -344,7 +341,9 @@
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -356,8 +355,10 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
-    "clear_cell": true,
-    "scrolled": true
+    "scrolled": true,
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
@@ -570,9 +571,11 @@
    "source": [
     "<div class=\"alert alert-success\">\n",
     "\n",
-    "<b>EXERCISE</b>:\n",
-    "<br><br>\n",
-    "Drop all 'flag' columns ('flag1', 'flag2', ...)"
+    "**EXERCISE**:\n",
+    "\n",
+    "Drop all 'flag' columns ('flag1', 'flag2', ...)\n",
+    "\n",
+    "</div>"
    ]
   },
   {
@@ -589,8 +592,10 @@
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
-    "clear_cell": true,
-    "scrolled": true
+    "scrolled": true,
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -912,7 +917,9 @@
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
@@ -1006,7 +1013,9 @@
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
@@ -1038,7 +1047,9 @@
    "cell_type": "code",
    "execution_count": 13,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
@@ -1134,7 +1145,9 @@
    "cell_type": "code",
    "execution_count": 14,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1146,7 +1159,9 @@
    "cell_type": "code",
    "execution_count": 15,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
@@ -1222,7 +1237,9 @@
    "cell_type": "code",
    "execution_count": 16,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1433,7 +1450,9 @@
    "cell_type": "code",
    "execution_count": 21,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1525,9 +1544,7 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {
-    "clear_cell": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1610,48 +1627,55 @@
    "source": [
     "<div class=\"alert alert-success\">\n",
     "\n",
-    "<b>EXERCISE</b>:\n",
+    "**EXERCISE**:\n",
     "\n",
-    " <ul>\n",
-    "  <li>Use the <code>glob.glob</code> function to list all 4 AirBase data files that are included in the 'data' directory, and call the result <code>data_files</code>.</li>\n",
-    "</ul>\n",
+    "Use the [pathlib module](https://docs.python.org/3/library/pathlib.html) `Path` class in combination with the `glob` method to list all 4 AirBase data files that are included in the 'data' directory, and call the result `data_files`.\n",
+    "\n",
+    "<details><summary>Hints</summary>\n",
+    "\n",
+    "- The pathlib module provides a object oriented way to handle file paths. First, create a `Path` object of the data folder, `pathlib.Path(\"./data\")`. Next, apply the `glob` function to extract all the files containing `*0008001*` (use wildcard * to say \"any characters\"). The output is a Python generator, which you can collect as a `list()`.\n",
+    "\n",
+    "</details>    \n",
+    "\n",
+    "    \n",
     "</div>"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "clear_cell": false
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "import glob"
+    "from pathlib import Path"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 10,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "['data/FR040120000800100hour.1-1-1999.31-12-2012',\n",
-       " 'data/FR040370000800100hour.1-1-1999.31-12-2012',\n",
-       " 'data/BETN0290000800100hour.1-1-1990.31-12-2012',\n",
-       " 'data/BETR8010000800100hour.1-1-1990.31-12-2012']"
+       "[PosixPath('data/BETN0290000800100hour.1-1-1990.31-12-2012'),\n",
+       " PosixPath('data/FR040120000800100hour.1-1-1999.31-12-2012'),\n",
+       " PosixPath('data/FR040370000800100hour.1-1-1999.31-12-2012'),\n",
+       " PosixPath('data/BETR8010000800100hour.1-1-1990.31-12-2012')]"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data_files = glob.glob(\"data/*0008001*\")\n",
+    "data_folder = Path(\"./data\")\n",
+    "data_files = list(data_folder.glob(\"*0008001*\"))\n",
     "data_files"
    ]
   },
@@ -1675,7 +1699,9 @@
    "cell_type": "code",
    "execution_count": 28,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1691,7 +1717,9 @@
    "cell_type": "code",
    "execution_count": 29,
    "metadata": {
-    "clear_cell": true
+    "tags": [
+     "nbtutor-solution"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1816,8 +1844,11 @@
   }
  ],
  "metadata": {
+  "jupytext": {
+   "formats": "ipynb,md:myst"
+  },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1831,7 +1862,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.7"
   },
   "nav_menu": {},
   "toc": {