Small fixes after course (clarify some instructions)

notebooks/pandas_06_data_cleaning.ipynb

@@ -2503,14 +2503,11 @@
     "\n",
     "<details><summary>Hints</summary>\n",
     "    \n",
-    "- Use the `rename` method and apply the mapping on the `columns`.\n",
-    "- The input of the `rename` method van be a dictionary or a function. Use the `clean_column_name` as the function to rename the columns. \n",
-    "- Make sure to explicitly set the columns= parameter.    \n",
+    "- To rename columns, we can use the `rename()` method.\n",
+    "- The input of the `rename()` method can also be a function in addition to a dictionary. When passing a function to `rename()`, pandas will under the hood call this function for each the column name individually, and use the return value as the renamed column name.\n",
+    "- Make sure to explicitly set the `columns=` parameter.    \n",
     "    \n",
-    "__NOTE__ The function `clean_column_name` takes as input a string and returns the string after removing the prefix and suffix. \n",
-    "\n",
-    "- The pandas method `rename` applies this function to each column name individually.    \n",
-    "- `removeprefix()` and `removesuffix()` are [Python string methods](https://docs.python.org/3/library/stdtypes.html#string-methods) to remove start/trailing characters if present.\n",
+    "__NOTE__ The function `clean_column_name` takes as input a string and returns the string after removing the prefix and suffix. `removeprefix()` and `removesuffix()` are [Python string methods](https://docs.python.org/3/library/stdtypes.html#string-methods) to remove start/trailing characters if present.\n",
     "\n",
     "</details>\n",
     "\n",
@@ -2524,10 +2521,27 @@
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'DAY_OF_WEEK'"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "def clean_column_name(name):\n",
-    "    return name.removeprefix(\"TX_\").removesuffix(\"_DESCR_NL\")"
+    "    \"\"\"\n",
+    "    Takes a string and returns it after removing \"TX_\" and \"_DESCR_NL\".\n",
+    "    \"\"\"\n",
+    "    return name.removeprefix(\"TX_\").removesuffix(\"_DESCR_NL\")\n",
+    "\n",
+    "# example to show what the 'clean_column_name' function does\n",
+    "clean_column_name(\"TX_DAY_OF_WEEK_DESCR_NL\")"
    ]
   },
   {

notebooks/pandas_06_data_cleaning.md

@@ -383,22 +383,25 @@ A number of the remaining metadata columns names have the `TX_` and the `_DESCR_
 
 <details><summary>Hints</summary>
 
-- Use the `rename` method and apply the mapping on the `columns`.
-- The input of the `rename` method van be a dictionary or a function. Use the `clean_column_name` as the function to rename the columns. 
-- Make sure to explicitly set the columns= parameter.    
+- To rename columns, we can use the `rename()` method.
+- The input of the `rename()` method can also be a function in addition to a dictionary. When passing a function to `rename()`, pandas will under the hood call this function for each the column name individually, and use the return value as the renamed column name.
+- Make sure to explicitly set the `columns=` parameter.    
 
-__NOTE__ The function `clean_column_name` takes as input a string and returns the string after removing the prefix and suffix. 
-
-- The pandas method `rename` applies this function to each column name individually.    
-- `removeprefix()` and `removesuffix()` are [Python string methods](https://docs.python.org/3/library/stdtypes.html#string-methods) to remove start/trailing characters if present.
+__NOTE__ The function `clean_column_name` takes as input a string and returns the string after removing the prefix and suffix. `removeprefix()` and `removesuffix()` are [Python string methods](https://docs.python.org/3/library/stdtypes.html#string-methods) to remove start/trailing characters if present.
 
 </details>
 
 </div>
 
 ```{code-cell} ipython3
 def clean_column_name(name):
+    """
+    Takes a string and returns it after removing "TX_" and "_DESCR_NL".
+    """
     return name.removeprefix("TX_").removesuffix("_DESCR_NL")
+
+# example to show what the 'clean_column_name' function does
+clean_column_name("TX_DAY_OF_WEEK_DESCR_NL")
 ```
 
 ```{code-cell} ipython3

notebooks/visualization_02_seaborn.ipynb

@@ -1558,9 +1558,10 @@
     "<details><summary>Hints</summary>\n",
     "\n",
     "- The sum of victims _for each_ hour of the day requires `groupby`. One can create a new column with the hour of the day or pass the hour directly to `groupby`.\n",
+    "- The groupby operation sets the key that you are grouping on as the index (row labels) of the result. The `reset_index()` method can be used to turn that index into normal dataframe columns.\n",
     "- The `.dt` accessor provides access to all kinds of datetime information.\n",
-    "- `rename` requires a dictionary with a mapping of the old vs new names.\n",
-    "- A bar plot is in seaborn one of the `catplot` options. \n",
+    "- `rename()` requires a dictionary with a mapping of the old to new names.\n",
+    "- A bar plot is in seaborn one of the `catplot()` options. \n",
     "    \n",
     "</details>"
    ]

notebooks/visualization_02_seaborn.md

@@ -434,9 +434,10 @@ Use the `height` and `aspect` to adjust the figure width/height.
 <details><summary>Hints</summary>
 
 - The sum of victims _for each_ hour of the day requires `groupby`. One can create a new column with the hour of the day or pass the hour directly to `groupby`.
+- The groupby operation sets the key that you are grouping on as the index (row labels) of the result. The `reset_index()` method can be used to turn that index into normal dataframe columns.
 - The `.dt` accessor provides access to all kinds of datetime information.
-- `rename` requires a dictionary with a mapping of the old vs new names.
-- A bar plot is in seaborn one of the `catplot` options. 
+- `rename()` requires a dictionary with a mapping of the old to new names.
+- A bar plot is in seaborn one of the `catplot()` options. 
 
 </details>