exam review

31729872 · Anna Meyer · a140f559 · 31729872 · 31729872
Commit 31729872 authored 1 year ago by Anna Meyer
--- a/sum23/lecture_materials/23_Plotting2/Exam Review.ipynb
+++ b/sum23/lecture_materials/23_Plotting2/Exam Review.ipynb
@@ -8,16 +8,18 @@
   "outputs": [],
   "source": [
    "import pandas as pd\n",
-    "from bs4 import BeautifulSoup"
+    "from bs4 import BeautifulSoup\n",
+    "import sqlite3"
   ]
  },
  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0c34e6b0",
+   "cell_type": "markdown",
+   "id": "5c9d1d79",
   "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "# Big picture review\n",
+    "Series vs dataframe vs database"
+   ]
  },
  {
   "cell_type": "code",
@@ -202,6 +204,45 @@
    "# get_text, children, attrs"
   ]
  },
+  {
+   "cell_type": "markdown",
+   "id": "753cf273",
+   "metadata": {},
+   "source": [
+    "# Databases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4fda7cf8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert os.path.exists(\"movies.db\")\n",
+    "conn = sqlite3.connect(\"movies.db\")\n",
+    "\n",
+    "def qry(QUERY):\n",
+    "    '''QUERY is a string containing SQL, conn is a global connection variable'''\n",
+    "    return pd.read_sql(QUERY, conn)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f98c2f0c",
+   "metadata": {},
+   "source": [
+    "where vs having"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a76a21e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
  {
   "cell_type": "markdown",
   "id": "984915b2",

 %% Cell type:code id:c3f52922 tags:

 ``` python
 import pandas as pd
 from bs4 import BeautifulSoup
+import sqlite3
 ```

-%% Cell type:code id:0c34e6b0 tags:
+%% Cell type:markdown id:5c9d1d79 tags:

-``` python
-```
+# Big picture review
+Series vs dataframe vs database

 %% Cell type:code id:69afd613 tags:

 ``` python
 ```

 %% Cell type:markdown id:e5f11a12 tags:

 # Pandas

 %% Cell type:code id:4ebb9401 tags:

 ``` python
 fish = {"Name":"fish", "color":"green", "length":8, "habitat":'water'}
 cat = {"Name":"cat","color":"brown","length":15,"habitat":'house'}
 tiger = {"Name":'tiger', 'color':'orange', 'length':48, 'habitat':'jungle'}
 dog = {"Name":'dog','color':'yellow','length':28,'habitat':'house'}

 animals = pd.DataFrame([fish,cat,tiger,dog])
 animals
 ```

 %% Cell type:code id:35f32b68 tags:

 ``` python
 # DataFrame vs Series
 ```

 %% Cell type:code id:a7bb549c tags:

 ``` python
 # Filtering - simple and complex conditions
 ```

 %% Cell type:code id:f6f7d185 tags:

 ``` python
 # Accessing individual values
 ```

 %% Cell type:code id:2f6f8f41 tags:

 ``` python
 # Understanding loc, iloc, and slicing
 ```

 %% Cell type:code id:62ccdd15 tags:

 ``` python
 # Setting an index column
 ```

 %% Cell type:markdown id:f9fdb089 tags:

 # Web

 %% Cell type:markdown id:b598dd65 tags:

 <table>
  <tr>
    <th>University</th>
    <th>Department</th>
  </tr>
  <tr>
    <td>UW-Madison</td>
    <td><a href = "https://www.cs.wisc.edu/">Computer Sciences</a></td>
  </tr>
  <tr>
    <td>UW-Madison</td>
    <td><a href = "https://stat.wisc.edu/">Statistics</a></td>
  </tr>
   <tr>
    <td>UW-Madison</td>
    <td><a href = "https://cdis.wisc.edu/">CDIS</a></td>
  </tr>
  <tr>
    <td>UC Berkeley</td>
    <td><a href = "https://eecs.berkeley.edu/">Electrical Engineering and Computer Sciences</a></td>
    </tr>
 </table>

 %% Cell type:code id:8b44c2dd tags:

 ``` python
 html_string = """
 <table>
  <tr>
    <th>University</th>
    <th>Department</th>
  </tr>
  <tr>
    <td>UW-Madison</td>
    <td><a href = "https://www.cs.wisc.edu/">Computer Sciences</a></td>
  </tr>
  <tr>
    <td>UW-Madison</td>
    <td><a href = "https://stat.wisc.edu/">Statistics</a></td>
  </tr>
   <tr>
    <td>UW-Madison</td>
    <td><a href = "https://cdis.wisc.edu/">CDIS</a></td>
  </tr>
  <tr>
    <td>UC Berkeley</td>
    <td>
    <a href = "https://eecs.berkeley.edu/">Electrical Engineering and Computer Sciences
    </a>
    </td>
    </tr>
 </table>
 """
 ```

 %% Cell type:code id:83ac470b tags:

 ``` python
 bs_obj = BeautifulSoup(html_string, 'html.parser')
 ```

 %% Cell type:code id:c546e7b8 tags:

 ``` python
 ```

 %% Cell type:code id:be3d05e0 tags:

 ``` python
 # get_text, children, attrs
 ```

+%% Cell type:markdown id:753cf273 tags:
+
+# Databases
+
+%% Cell type:code id:4fda7cf8 tags:
+
+``` python
+assert os.path.exists("movies.db")
+conn = sqlite3.connect("movies.db")
+
+def qry(QUERY):
+    '''QUERY is a string containing SQL, conn is a global connection variable'''
+    return pd.read_sql(QUERY, conn)
+```
+
+%% Cell type:markdown id:f98c2f0c tags:
+
+where vs having
+
+%% Cell type:code id:a76a21e2 tags:
+
+``` python
+```
+
 %% Cell type:markdown id:984915b2 tags:

 # Review

 %% Cell type:markdown id:f4fc528d tags:

 Code flow

 %% Cell type:code id:aba2a0a6 tags:

 ``` python
 # Look at examples with python tutor
 #. #  if/elif/else
 #. #  try/except
 #  #. simple recursive function
 ```

 %% Cell type:markdown id:5435a2eb tags:

 Parameters and functions

 %% Cell type:code id:fc8d4c25 tags:

 ``` python
 def greeting(name, salutation = 'Hello', punctuation='!'):
    print(salutation, name, punctuation)
 ```

 %% Cell type:code id:8bd6614f tags:

 ``` python
 ```

--- a/sum23/lecture_materials/23_Plotting2/movies.db
+++ b/sum23/lecture_materials/23_Plotting2/movies.db