diff --git a/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb b/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
index c4bd3e90cc64459f8705b6d7ec6c38dafb180682..1448f33090fe73ef340591659ef141bcfa3809f3 100644
--- a/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
+++ b/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
@@ -156,21 +156,138 @@
"metadata": {},
"source": [
"In this problem you will have to make use of **Pandas** to load and analyse a small, fictional database weather.csv (the same as used in the Script).\n",
- "The data containes the temperature in 4 cities over 6 months. Download the dataset and save it somewhere practically, possibly in the same folder as this notebook."
+ "The data containes the temperature in 4 cities over 6 months. Download the dataset and save it somewhere practical, possibly in the same folder as this notebook."
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 11,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting pandas\n",
+ " Downloading pandas-1.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (11.7 MB)\n",
+ "\u001b[2K \u001b[90mâ”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”â”\u001b[0m \u001b[32m11.7/11.7 MB\u001b[0m \u001b[31m26.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m0:01\u001b[0m\n",
+ "\u001b[?25hRequirement already satisfied: numpy>=1.18.5 in /opt/conda/lib/python3.9/site-packages (from pandas) (1.22.3)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /opt/conda/lib/python3.9/site-packages (from pandas) (2021.3)\n",
+ "Requirement already satisfied: python-dateutil>=2.8.1 in /opt/conda/lib/python3.9/site-packages (from pandas) (2.8.2)\n",
+ "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.9/site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n",
+ "Installing collected packages: pandas\n",
+ "Successfully installed pandas-1.4.1\n",
+ "\u001b[33mWARNING: You are using pip version 22.0.3; however, version 22.0.4 is available.\n",
+ "You should consider upgrading via the '/opt/conda/bin/python -m pip install --upgrade pip' command.\u001b[0m\u001b[33m\n",
+ "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
+ ]
+ }
+ ],
+ "source": [
+ "pip install pandas"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Luzern</th>\n",
+ " <th>Basel</th>\n",
+ " <th>Chur</th>\n",
+ " <th>Zurich</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Jan</th>\n",
+ " <td>2</td>\n",
+ " <td>5</td>\n",
+ " <td>-3</td>\n",
+ " <td>4</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Feb</th>\n",
+ " <td>5</td>\n",
+ " <td>6</td>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Mar</th>\n",
+ " <td>10</td>\n",
+ " <td>11</td>\n",
+ " <td>13</td>\n",
+ " <td>8</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Apr</th>\n",
+ " <td>16</td>\n",
+ " <td>12</td>\n",
+ " <td>14</td>\n",
+ " <td>17</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>May</th>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>21</td>\n",
+ " <td>20</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jun</th>\n",
+ " <td>25</td>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>27</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Luzern Basel Chur Zurich\n",
+ "Jan 2 5 -3 4\n",
+ "Feb 5 6 1 0\n",
+ "Mar 10 11 13 8\n",
+ "Apr 16 12 14 17\n",
+ "May 21 23 21 20\n",
+ "Jun 25 21 23 27"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"# First import Pandas\n",
"import pandas as pd\n",
"\n",
"# load the database using pandas.read_csv. The file location is different for everyone. If you made a new folder in this folder named \"data\", the path would be ./data/weather.csv\n",
"# Example: data = pd.read_csv(\"/data/weather.csv\")\n",
- "data = None\n",
+ "data = pd.read_csv(\"./data/weather.csv\")\n",
"\n",
"data"
]
@@ -193,7 +310,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 31,
"metadata": {},
"outputs": [
{
@@ -201,16 +318,22 @@
"output_type": "stream",
"text": [
"Temperature in Basel is:\n",
- " None \n",
+ " Jan 5\n",
+ "Feb 6\n",
+ "Mar 11\n",
+ "Apr 12\n",
+ "May 23\n",
+ "Jun 21\n",
+ "Name: Basel, dtype: int64 \n",
"\n",
"Temperature in Chur in February is:\n",
- " None\n"
+ " 1\n"
]
}
],
"source": [
- "t_basel = None\n",
- "t_chur_feb = None\n",
+ "t_basel = data.loc[:, \"Basel\"]\n",
+ "t_chur_feb = data.loc[\"Feb\", \"Chur\"]\n",
"\n",
"print(\"Temperature in Basel is:\\n\", t_basel, \"\\n\")\n",
"print(\"Temperature in Chur in February is:\\n\", t_chur_feb)"
@@ -234,23 +357,112 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "None\n"
+ "Zurich\n"
]
+ },
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Luzern</th>\n",
+ " <th>Bern</th>\n",
+ " <th>Chur</th>\n",
+ " <th>Zurich</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Jan</th>\n",
+ " <td>2</td>\n",
+ " <td>5</td>\n",
+ " <td>-3</td>\n",
+ " <td>4</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Feb</th>\n",
+ " <td>5</td>\n",
+ " <td>6</td>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Mar</th>\n",
+ " <td>10</td>\n",
+ " <td>11</td>\n",
+ " <td>13</td>\n",
+ " <td>8</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Apr</th>\n",
+ " <td>16</td>\n",
+ " <td>12</td>\n",
+ " <td>14</td>\n",
+ " <td>17</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>May</th>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>21</td>\n",
+ " <td>20</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jun</th>\n",
+ " <td>25</td>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>27</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Luzern Bern Chur Zurich\n",
+ "Jan 2 5 -3 4\n",
+ "Feb 5 6 1 0\n",
+ "Mar 10 11 13 8\n",
+ "Apr 16 12 14 17\n",
+ "May 21 23 21 20\n",
+ "Jun 25 21 23 27"
+ ]
+ },
+ "execution_count": 37,
+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
"# Find the name of column 3:\n",
- "name_c3 = None\n",
+ "name_c3 = data.columns[3]\n",
"print(name_c3)\n",
" \n",
"# Change \"Basel\" to \"Bern\"\n",
+ "data = data.rename(columns={\"Basel\": \"Bern\"})\n",
"\n",
"data"
]
@@ -267,24 +479,24 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Average temperature in Chur was: None\n",
- "Average temperature in Spring was: 0\n"
+ "Average temperature in Chur was: 11.5\n",
+ "Average temperature in Spring was: 15.5\n"
]
}
],
"source": [
- "t_chur_mean = None\n",
+ "t_chur_mean = data.loc[:, \"Chur\"].mean()\n",
"\n",
"\n",
- "t_spring_mean = 0\n",
- "# Hint: mean() on a DataFrame gives the result in a Serries. The axis of the function to be applied on can be set with axis={index (0), columns (1)}.\n",
+ "t_spring_mean = data.loc[\"Mar\":\"May\", :].mean().mean()\n",
+ "# Hint: mean() on a DataFrame gives the result in a Series. The axis of the function to be applied on can be set with axis={index (0), columns (1)}.\n",
"# To find the mean of the whole matrix, the mean method can be applied twice\n",
"\n",
"\n",
@@ -303,20 +515,201 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 41,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Luzern</th>\n",
+ " <th>Bern</th>\n",
+ " <th>Chur</th>\n",
+ " <th>Zurich</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>Feb</th>\n",
+ " <td>5</td>\n",
+ " <td>6</td>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jan</th>\n",
+ " <td>2</td>\n",
+ " <td>5</td>\n",
+ " <td>-3</td>\n",
+ " <td>4</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Mar</th>\n",
+ " <td>10</td>\n",
+ " <td>11</td>\n",
+ " <td>13</td>\n",
+ " <td>8</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Apr</th>\n",
+ " <td>16</td>\n",
+ " <td>12</td>\n",
+ " <td>14</td>\n",
+ " <td>17</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>May</th>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>21</td>\n",
+ " <td>20</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jun</th>\n",
+ " <td>25</td>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>27</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Luzern Bern Chur Zurich\n",
+ "Feb 5 6 1 0\n",
+ "Jan 2 5 -3 4\n",
+ "Mar 10 11 13 8\n",
+ "Apr 16 12 14 17\n",
+ "May 21 23 21 20\n",
+ "Jun 25 21 23 27"
+ ]
+ },
+ "execution_count": 41,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "# Sort data based on Zurich"
+ "# Sort data based on Zurich\n",
+ "data.sort_values(\"Zurich\")"
]
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 43,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Luzern</th>\n",
+ " <th>Basel</th>\n",
+ " <th>Chur</th>\n",
+ " <th>Zurich</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>May</th>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>21</td>\n",
+ " <td>20</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jun</th>\n",
+ " <td>25</td>\n",
+ " <td>21</td>\n",
+ " <td>23</td>\n",
+ " <td>27</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Apr</th>\n",
+ " <td>16</td>\n",
+ " <td>12</td>\n",
+ " <td>14</td>\n",
+ " <td>17</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Mar</th>\n",
+ " <td>10</td>\n",
+ " <td>11</td>\n",
+ " <td>13</td>\n",
+ " <td>8</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Feb</th>\n",
+ " <td>5</td>\n",
+ " <td>6</td>\n",
+ " <td>1</td>\n",
+ " <td>0</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>Jan</th>\n",
+ " <td>2</td>\n",
+ " <td>5</td>\n",
+ " <td>-3</td>\n",
+ " <td>4</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Luzern Basel Chur Zurich\n",
+ "May 21 23 21 20\n",
+ "Jun 25 21 23 27\n",
+ "Apr 16 12 14 17\n",
+ "Mar 10 11 13 8\n",
+ "Feb 5 6 1 0\n",
+ "Jan 2 5 -3 4"
+ ]
+ },
+ "execution_count": 43,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "# Sort data based on Basel, descending with temperature"
+ "# Sort data based on Basel, descending with temperature\n",
+ "data = data.rename(columns={\"Bern\": \"Basel\"})\n",
+ "data.sort_values(\"Basel\", ascending=False)"
]
},
{