diff --git a/notebooks/get_data_notebook.ipynb b/notebooks/get_data_notebook.ipynb
deleted file mode 100644
index c3b6ad0..0000000
--- a/notebooks/get_data_notebook.ipynb
+++ /dev/null
@@ -1,548 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Velg start dato og sluttdato\n",
-    "\n",
-    "For å kunne hente data og gjøre en analyse trenger programmet å vite hvilken periode du vil hente ut for.\n",
-    "\n",
-    "Dataen skrives inn slik: (yyyy, mm, dd, hh, mm)\n",
-    "Her følger et eksempel:  \n",
-    "|Hva|Hvordan|Eksempel|\n",
-    "|:---|:---:|:---:|\n",
-    "|år|yyyy|2025|\n",
-    "|måned|mm|03| \n",
-    "|dato|dd|01|  \n",
-    "|time|hh|12| \n",
-    "|minutt|mm|00|   \n",
-    "\n",
-    "Denne dataen skrives da inn på følgende hvis: (2025, 03, 01, 12, 00)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Start date => unix timestamp: 1742202600\n",
-      "End date => unix timestamp: 1742548200\n",
-      "Unix timestamp => start date: 2025-03-17 10:10:00\n",
-      "Unix timestamp => end date: 2025-03-21 10:10:00\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import os\n",
-    "\n",
-    "# Gets the absolute path to the src folder\n",
-    "sys.path.append(os.path.abspath(\"../src\"))\n",
-    "\n",
-    "# Now we can import the fucntion from the module\n",
-    "from my_package.date_to_unix import get_unix_timestamp\n",
-    "from my_package.date_to_unix import from_unix_timestamp\n",
-    "\n",
-    "# Runs the function and store the data\n",
-    "unix_start_date, unix_end_date = get_unix_timestamp()\n",
-    "\n",
-    "# Prints the unix_timestamp\n",
-    "print(\"Start date => unix timestamp:\", unix_start_date)\n",
-    "print(\"End date => unix timestamp:\", unix_end_date)\n",
-    "\n",
-    "# Run the function to convert from unix_timestamp to date, and store the variables\n",
-    "start_date, end_date = from_unix_timestamp(unix_start_date, unix_end_date)\n",
-    "\n",
-    "# prints the date\n",
-    "print(\"Unix timestamp => start date:\", start_date)\n",
-    "print(\"Unix timestamp => end date:\", end_date)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Velg et sted i Norge og få data\n",
-    "\n",
-    "Skriv inn et sted du ønsker data fra, foreløpig er det begrenset til Norge\n",
-    "\n",
-    "Programmet vil deretter hente data å lagre det i en json fil"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data fetch: ok\n"
-     ]
-    }
-   ],
-   "source": [
-    "import sys\n",
-    "import os\n",
-    "\n",
-    "# Gets the absolute path to the src folder\n",
-    "sys.path.append(os.path.abspath(\"../src\"))\n",
-    "\n",
-    "# Now we can import the fucntion from the module\n",
-    "from my_package.fetch_data import fetch_data\n",
-    "\n",
-    "# User input the city, for the weather\n",
-    "city_name = input(\"Enter a city in Norway: \")\n",
-    "\n",
-    "data = fetch_data(unix_start_date, unix_end_date, city_name)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Lagre data i en json-fil\n",
-    "\n",
-    "Skriv inn navn for til filen du vil lagre med dataen.\n",
-    "\n",
-    "Eks. test\n",
-    "Da vil filen lagres som data_**test**.json, i mappen \"../data/output_stedsnavn/data_{filnavn}.json\"\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data has been written to /Users/toravestlund/Documents/ITBAITBEDR/TDT4114 - Anvendt programmering/anvendt_mappe/data/output_stedsdata/data_test6.json\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Gets the absolute path to the src folder\n",
-    "sys.path.append(os.path.abspath(\"../src\"))\n",
-    "\n",
-    "from my_package.write_data import write_data\n",
-    "\n",
-    "filename = input(\"Write filename: \")\n",
-    "\n",
-    "write_data(data, filename)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Lese fra fil\n",
-    "\n",
-    "Henter opp data lagret i filen, lagd over, og skriver ut lesbart ved hjelp av pandas"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "      message  cod  city_id  calctime  cnt  \\\n",
-      "0   Count: 96  200  3133880  0.021173   96   \n",
-      "1   Count: 96  200  3133880  0.021173   96   \n",
-      "2   Count: 96  200  3133880  0.021173   96   \n",
-      "3   Count: 96  200  3133880  0.021173   96   \n",
-      "4   Count: 96  200  3133880  0.021173   96   \n",
-      "..        ...  ...      ...       ...  ...   \n",
-      "91  Count: 96  200  3133880  0.021173   96   \n",
-      "92  Count: 96  200  3133880  0.021173   96   \n",
-      "93  Count: 96  200  3133880  0.021173   96   \n",
-      "94  Count: 96  200  3133880  0.021173   96   \n",
-      "95  Count: 96  200  3133880  0.021173   96   \n",
-      "\n",
-      "                                                 list  \n",
-      "0   {'dt': 1742205600, 'main': {'temp': 1.98, 'fee...  \n",
-      "1   {'dt': 1742209200, 'main': {'temp': 3.05, 'fee...  \n",
-      "2   {'dt': 1742212800, 'main': {'temp': 3.6, 'feel...  \n",
-      "3   {'dt': 1742216400, 'main': {'temp': 4.16, 'fee...  \n",
-      "4   {'dt': 1742220000, 'main': {'temp': 4.11, 'fee...  \n",
-      "..                                                ...  \n",
-      "91  {'dt': 1742533200, 'main': {'temp': -0.24, 'fe...  \n",
-      "92  {'dt': 1742536800, 'main': {'temp': -0.24, 'fe...  \n",
-      "93  {'dt': 1742540400, 'main': {'temp': 0.62, 'fee...  \n",
-      "94  {'dt': 1742544000, 'main': {'temp': 2.18, 'fee...  \n",
-      "95  {'dt': 1742547600, 'main': {'temp': 5.03, 'fee...  \n",
-      "\n",
-      "[96 rows x 6 columns]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "\n",
-    "data = pd.read_json(f'../data/output_stedsdata/data_{filename}.json')\n",
-    "\n",
-    "print(data)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "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>main.temp</th>\n",
-       "      <th>main.feels_like</th>\n",
-       "      <th>main.pressure</th>\n",
-       "      <th>main.humidity</th>\n",
-       "      <th>main.temp_min</th>\n",
-       "      <th>main.temp_max</th>\n",
-       "      <th>wind.speed</th>\n",
-       "      <th>wind.deg</th>\n",
-       "      <th>wind.gust</th>\n",
-       "      <th>clouds.all</th>\n",
-       "      <th>rain.1h</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>dt</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2025-03-17 10:00:00</th>\n",
-       "      <td>1.98</td>\n",
-       "      <td>0.11</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>92</td>\n",
-       "      <td>1.07</td>\n",
-       "      <td>2.77</td>\n",
-       "      <td>1.79</td>\n",
-       "      <td>203</td>\n",
-       "      <td>3.58</td>\n",
-       "      <td>100</td>\n",
-       "      <td>0.36</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-17 11:00:00</th>\n",
-       "      <td>3.05</td>\n",
-       "      <td>0.84</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>93</td>\n",
-       "      <td>2.73</td>\n",
-       "      <td>3.33</td>\n",
-       "      <td>2.24</td>\n",
-       "      <td>225</td>\n",
-       "      <td>5.36</td>\n",
-       "      <td>100</td>\n",
-       "      <td>0.79</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-17 12:00:00</th>\n",
-       "      <td>3.60</td>\n",
-       "      <td>1.49</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>91</td>\n",
-       "      <td>3.03</td>\n",
-       "      <td>3.88</td>\n",
-       "      <td>2.24</td>\n",
-       "      <td>248</td>\n",
-       "      <td>4.02</td>\n",
-       "      <td>100</td>\n",
-       "      <td>1.38</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-17 13:00:00</th>\n",
-       "      <td>4.16</td>\n",
-       "      <td>1.75</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>92</td>\n",
-       "      <td>3.84</td>\n",
-       "      <td>4.44</td>\n",
-       "      <td>2.68</td>\n",
-       "      <td>270</td>\n",
-       "      <td>8.05</td>\n",
-       "      <td>100</td>\n",
-       "      <td>0.16</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-17 14:00:00</th>\n",
-       "      <td>4.11</td>\n",
-       "      <td>0.75</td>\n",
-       "      <td>1021</td>\n",
-       "      <td>89</td>\n",
-       "      <td>3.88</td>\n",
-       "      <td>5.03</td>\n",
-       "      <td>4.02</td>\n",
-       "      <td>293</td>\n",
-       "      <td>8.05</td>\n",
-       "      <td>100</td>\n",
-       "      <td>0.14</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-21 05:00:00</th>\n",
-       "      <td>-0.24</td>\n",
-       "      <td>-2.29</td>\n",
-       "      <td>1024</td>\n",
-       "      <td>91</td>\n",
-       "      <td>-1.16</td>\n",
-       "      <td>0.55</td>\n",
-       "      <td>1.67</td>\n",
-       "      <td>122</td>\n",
-       "      <td>1.86</td>\n",
-       "      <td>42</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-21 06:00:00</th>\n",
-       "      <td>-0.24</td>\n",
-       "      <td>-2.14</td>\n",
-       "      <td>1024</td>\n",
-       "      <td>90</td>\n",
-       "      <td>-1.16</td>\n",
-       "      <td>0.55</td>\n",
-       "      <td>1.57</td>\n",
-       "      <td>136</td>\n",
-       "      <td>1.67</td>\n",
-       "      <td>44</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-21 07:00:00</th>\n",
-       "      <td>0.62</td>\n",
-       "      <td>-0.97</td>\n",
-       "      <td>1025</td>\n",
-       "      <td>89</td>\n",
-       "      <td>-0.60</td>\n",
-       "      <td>2.03</td>\n",
-       "      <td>1.45</td>\n",
-       "      <td>125</td>\n",
-       "      <td>1.77</td>\n",
-       "      <td>97</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-21 08:00:00</th>\n",
-       "      <td>2.18</td>\n",
-       "      <td>0.78</td>\n",
-       "      <td>1025</td>\n",
-       "      <td>92</td>\n",
-       "      <td>2.18</td>\n",
-       "      <td>3.03</td>\n",
-       "      <td>1.47</td>\n",
-       "      <td>94</td>\n",
-       "      <td>1.99</td>\n",
-       "      <td>88</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2025-03-21 09:00:00</th>\n",
-       "      <td>5.03</td>\n",
-       "      <td>3.85</td>\n",
-       "      <td>1025</td>\n",
-       "      <td>78</td>\n",
-       "      <td>5.03</td>\n",
-       "      <td>5.03</td>\n",
-       "      <td>1.60</td>\n",
-       "      <td>85</td>\n",
-       "      <td>2.29</td>\n",
-       "      <td>67</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>96 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                     main.temp  main.feels_like  main.pressure  main.humidity  \\\n",
-       "dt                                                                              \n",
-       "2025-03-17 10:00:00       1.98             0.11           1021             92   \n",
-       "2025-03-17 11:00:00       3.05             0.84           1021             93   \n",
-       "2025-03-17 12:00:00       3.60             1.49           1021             91   \n",
-       "2025-03-17 13:00:00       4.16             1.75           1021             92   \n",
-       "2025-03-17 14:00:00       4.11             0.75           1021             89   \n",
-       "...                        ...              ...            ...            ...   \n",
-       "2025-03-21 05:00:00      -0.24            -2.29           1024             91   \n",
-       "2025-03-21 06:00:00      -0.24            -2.14           1024             90   \n",
-       "2025-03-21 07:00:00       0.62            -0.97           1025             89   \n",
-       "2025-03-21 08:00:00       2.18             0.78           1025             92   \n",
-       "2025-03-21 09:00:00       5.03             3.85           1025             78   \n",
-       "\n",
-       "                     main.temp_min  main.temp_max  wind.speed  wind.deg  \\\n",
-       "dt                                                                        \n",
-       "2025-03-17 10:00:00           1.07           2.77        1.79       203   \n",
-       "2025-03-17 11:00:00           2.73           3.33        2.24       225   \n",
-       "2025-03-17 12:00:00           3.03           3.88        2.24       248   \n",
-       "2025-03-17 13:00:00           3.84           4.44        2.68       270   \n",
-       "2025-03-17 14:00:00           3.88           5.03        4.02       293   \n",
-       "...                            ...            ...         ...       ...   \n",
-       "2025-03-21 05:00:00          -1.16           0.55        1.67       122   \n",
-       "2025-03-21 06:00:00          -1.16           0.55        1.57       136   \n",
-       "2025-03-21 07:00:00          -0.60           2.03        1.45       125   \n",
-       "2025-03-21 08:00:00           2.18           3.03        1.47        94   \n",
-       "2025-03-21 09:00:00           5.03           5.03        1.60        85   \n",
-       "\n",
-       "                     wind.gust  clouds.all  rain.1h  \n",
-       "dt                                                   \n",
-       "2025-03-17 10:00:00       3.58         100     0.36  \n",
-       "2025-03-17 11:00:00       5.36         100     0.79  \n",
-       "2025-03-17 12:00:00       4.02         100     1.38  \n",
-       "2025-03-17 13:00:00       8.05         100     0.16  \n",
-       "2025-03-17 14:00:00       8.05         100     0.14  \n",
-       "...                        ...         ...      ...  \n",
-       "2025-03-21 05:00:00       1.86          42      NaN  \n",
-       "2025-03-21 06:00:00       1.67          44      NaN  \n",
-       "2025-03-21 07:00:00       1.77          97      NaN  \n",
-       "2025-03-21 08:00:00       1.99          88      NaN  \n",
-       "2025-03-21 09:00:00       2.29          67      NaN  \n",
-       "\n",
-       "[96 rows x 11 columns]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "\n",
-    "data = pd.read_json(f'../data/output_stedsdata/data_{filename}.json')\n",
-    "\n",
-    "if 'list' in data:\n",
-    "    df = pd.json_normalize(data['list'])\n",
-    "\n",
-    "    # Delete duplicates based on the dt row, all the other values can appear more than once, but the date should only appear once\n",
-    "    df = df.drop_duplicates(subset=['dt'])\n",
-    "\n",
-    "    # The weather column dosnt have any releated information, therefor we delete it\n",
-    "    df = df.drop(columns=\"weather\")\n",
-    "\n",
-    "    # Convert 'dt' column from Unix timestamp to datetime and set it as the index\n",
-    "    df['dt'] = pd.to_datetime(df['dt'], unit='s')\n",
-    "    df.set_index('dt', inplace=True)\n",
-    "   \n",
-    "\n",
-    "   \n",
-    "\n",
-    "    # Ensure the DataFrame is displayed correctly\n",
-    "    display(df)\n",
-    "\n",
-    "    # # Extract main values\n",
-    "    # temp = df['main.temp']\n",
-    "    # humidity = df['main.humidity']\n",
-    "\n",
-    "    # # Extract wind values\n",
-    "    # w_speed = df['wind.speed']\n",
-    "\n",
-    "    # # Extract other variables\n",
-    "    # clouds = df['clouds.all']\n",
-    "\n",
-    "    # try:\n",
-    "    #     rain = df['rain.1h']\n",
-    "    # except KeyError:\n",
-    "    #     print(\"'Rain' is not present in the JSON file.\")\n",
-    "\n",
-    "    # try:\n",
-    "    #     snow = df['snow.1h']\n",
-    "    # except KeyError:\n",
-    "    #     print(\"'Snow' is not present in the JSON file.\")\n",
-    "\n",
-    "    # # Print the average temperature\n",
-    "    # print('Gjennomsnitts temperatur: ', temp.mean().round(2))\n",
-    "\n",
-    "    # Display the temperature column\n",
-    "    # display(temp)\n",
-    "else:\n",
-    "    print(\"The 'list' key is not present in the JSON file.\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# \"komprimere oversikten over\"\n",
-    "# Som i å, finne gjennomsnitt av alle aktuelle data, \n",
-    "# høyeste, laveste (spesielt temp) i gitte periode"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.5"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/notebooks/notebook_one_day_data.ipynb b/notebooks/notebook_one_day_data.ipynb
index d2972f8..1083d65 100644
--- a/notebooks/notebook_one_day_data.ipynb
+++ b/notebooks/notebook_one_day_data.ipynb
@@ -182,7 +182,9 @@
    "metadata": {},
    "source": [
     "### Viser temperaturen\n",
-    "Regner ut gjennomsnittst-temperatur ved hjelp av innebygde funksjoner. Finner også høyeste og laveste målte temperatur."
+    "Regner ut gjennomsnittst-temperatur ved hjelp av innebygde funksjoner. Finner også høyeste og laveste målte temperatur.\n",
+    "\n",
+    "Plotter temperaturen ved hjelp av matplotlib."
    ]
   },
   {
@@ -191,6 +193,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as mdates\n",
+    "\n",
     "# Stores the temperature values\n",
     "temp = df['main.temp']\n",
     "\n",
@@ -204,7 +209,38 @@
     "min_temp = df['main.temp'].min().round(2)\n",
     "\n",
     "print(\"Highest temperature:\", max_temp)\n",
-    "print(\"Lowest temperature:\", min_temp)"
+    "print(\"Lowest temperature:\", min_temp)\n",
+    "\n",
+    "# Set the x_axis to the index, which means the time\n",
+    "x_axis = df.index\n",
+    "\n",
+    "# Choose the width and height of the plot\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "\n",
+    "# Plotting temperatur\n",
+    "plt.plot(x_axis, temp, color='tab:red', label='Temperatur')\n",
+    "\n",
+    "# Get the current axsis, and store it as ax\n",
+    "ax = plt.gca()\n",
+    "\n",
+    "# Customize the x-axis to show ticks for each hour\n",
+    "ax.xaxis.set_major_locator(mdates.HourLocator(interval=1))  # Tick marks for every hour\n",
+    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))  # Format as \"Day Month Hour:Minute\"\n",
+    "\n",
+    "# Adjust layout\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Add title for the plot, with city_name and start to end date\n",
+    "plt.title(f'Temperatur {city_name}, ({date})')\n",
+    "\n",
+    "# Shows a grid\n",
+    "plt.grid()\n",
+    "\n",
+    "# Show the label-description\n",
+    "plt.legend(loc = 'upper right')\n",
+    "\n",
+    "# Show the plot\n",
+    "plt.show()"
    ]
   },
   {
@@ -266,7 +302,10 @@
     "ax.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))\n",
     "\n",
     "# Add the label-desciption\n",
-    "plt.legend()\n",
+    "plt.legend(loc = 'upper right')\n",
+    "\n",
+    "# Add title to the plot, with date\n",
+    "plt.title(f'Precipitation {city_name}, ({date}))')\n",
     "\n",
     "# Shows the plot\n",
     "plt.show()"
@@ -405,7 +444,6 @@
     "# Two vertically stacked axis, (2 rows, 1 column), width and height of the figure, and the axis share the same x_axis\n",
     "fig, (ax1, ax3) = plt.subplots(2, 1,figsize=(15, 8), sharex=True)\n",
     "\n",
-    "\n",
     "# Set the title for the diagram, above the first axis, with city_name and input_date\n",
     "ax1.set_title(f'Weather data for {city_name} ({date}) ')\n",
     "\n",
@@ -429,7 +467,6 @@
     "ax2.set_ylabel(\"Precipitation (mm)\", color='tab:blue')\n",
     "ax2.tick_params(axis='y', labelcolor='tab:blue')\n",
     "\n",
-    "\n",
     "# Format the x-axis to show all hours, in the format \"HH:MM\"\n",
     "ax1.xaxis.set_major_locator(mdates.HourLocator()) \n",
     "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%H:%M'))\n",
@@ -441,7 +478,6 @@
     "# Add grid, but only vertically\n",
     "ax1.grid(axis = 'x')\n",
     "\n",
-    "\n",
     "# Plot the wind at the second x-axis (the axis below)\n",
     "ax3.plot(x_axis, wind_gust, color='tab:purple', label='Wind_gust')\n",
     "ax3.plot(x_axis, wind_speed, color='tab:purple', linestyle='dashed', label='Wind_speed')\n",
@@ -467,7 +503,6 @@
     "plot_path = os.path.join(output_folder, f\"weather_data_plot{city_name}.png\")\n",
     "plt.savefig(plot_path)  # Save the plot as a PNG file\n",
     "\n",
-    "\n",
     "# Show the plot\n",
     "plt.show()"
    ]
diff --git a/notebooks/notebook_one_week_data.ipynb b/notebooks/notebook_one_week_data.ipynb
new file mode 100644
index 0000000..5d43ebc
--- /dev/null
+++ b/notebooks/notebook_one_week_data.ipynb
@@ -0,0 +1,540 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Notebook - One week data\n",
+    "Denne notebooken henter data fra ønsket periode (inntil 7-dager) og sted, skriver til fil. Visualiserer manglende verdier, retter opp manglende verdier, og visualisere og lagrer data fra plot."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Velg start dato og sluttdato\n",
+    "\n",
+    "For å kunne hente data og gjøre en analyse trenger programmet å vite hvilken periode du vil hente ut for.\n",
+    "\n",
+    "Dataen skrives inn slik: (yyyy, mm, dd, hh, mm)\n",
+    "Her følger et eksempel:  \n",
+    "|Hva|Hvordan|Eksempel|\n",
+    "|:---|:---:|:---:|\n",
+    "|år|yyyy|2025|\n",
+    "|måned|mm|03| \n",
+    "|dato|dd|01|  \n",
+    "|time|hh|12| \n",
+    "|minutt|mm|00|   \n",
+    "\n",
+    "Denne dataen skrives da inn på følgende hvis: (2025, 03, 01, 12, 00)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Gets the absolute path to the src folder\n",
+    "sys.path.append(os.path.abspath(\"../src\"))\n",
+    "\n",
+    "# Now we can import the fucntion from the module\n",
+    "from my_package.date_to_unix import get_unix_timestamp\n",
+    "from my_package.date_to_unix import from_unix_timestamp\n",
+    "\n",
+    "# Runs the function and store the data\n",
+    "unix_start_date, unix_end_date = get_unix_timestamp()\n",
+    "\n",
+    "# Prints the unix_timestamp\n",
+    "print(\"Start date => unix timestamp:\", unix_start_date)\n",
+    "print(\"End date => unix timestamp:\", unix_end_date)\n",
+    "\n",
+    "# Run the function to convert from unix_timestamp to date, and store the variables\n",
+    "start_date, end_date = from_unix_timestamp(unix_start_date, unix_end_date)\n",
+    "\n",
+    "# Prints the date\n",
+    "print(\"Unix timestamp => start date:\", start_date)\n",
+    "print(\"Unix timestamp => end date:\", end_date)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Velg et sted i Norge og få data\n",
+    "\n",
+    "Skriv inn et sted du ønsker data fra, foreløpig er det begrenset til Norge\n",
+    "\n",
+    "Programmet vil deretter hente data å lagre det i en json fil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "\n",
+    "# Gets the absolute path to the src folder\n",
+    "sys.path.append(os.path.abspath(\"../src\"))\n",
+    "\n",
+    "# Now we can import the fucntion from the module\n",
+    "from my_package.fetch_data import fetch_data\n",
+    "\n",
+    "# User input the city, for the weather\n",
+    "city_name = input(\"Enter a city in Norway: \")\n",
+    "\n",
+    "# Stores the values in the variables\n",
+    "data, folder = fetch_data(unix_start_date, unix_end_date, city_name)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Lagre data i en json-fil\n",
+    "\n",
+    "Skriv inn navn for til filen du vil lagre med dataen.\n",
+    "\n",
+    "Eks. test\n",
+    "Da vil filen lagres som data_**test**.json, i mappen \"../data/output_stedsnavn/data_{filnavn}.json\"\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Gets the absolute path to the src folder\n",
+    "sys.path.append(os.path.abspath(\"../src\"))\n",
+    "\n",
+    "from my_package.write_data import write_data\n",
+    "\n",
+    "# User chose the name for the file\n",
+    "filename = input(\"Write filename: \")\n",
+    "\n",
+    "# Write the data, with the choosen filename\n",
+    "write_data(data, folder, filename)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Lese fra fil\n",
+    "\n",
+    "Henter opp data lagret i filen, lagd over, og skriver ut lesbart ved hjelp av pandas"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Read json-file using pandas\n",
+    "data = pd.read_json(f'../data/output_stedsnavn/data_{filename}.json')\n",
+    "\n",
+    "# Display the data\n",
+    "display(data)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Rensking av riktig data\n",
+    "Vi går inn i 'list' for å finne den relevante informasjonen, og ikke bare meta-informasjon.\n",
+    "\n",
+    "Sørger for å fjerne duplikater, og andre irelevante kolonner. Samt setter index kolonnen til tid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Goes into the 'list' to get the needed and relevant information\n",
+    "if 'list' in data:\n",
+    "    # Normalize the json, for better readability\n",
+    "    df = pd.json_normalize(data['list'])\n",
+    "\n",
+    "    # Delete duplicates based on the dt row, all the other values can appear more than once, but the date should only appear once\n",
+    "    df = df.drop_duplicates(subset=['dt'])\n",
+    "\n",
+    "    # The weather column does not have any releated information, therefor we delete it\n",
+    "    df = df.drop(columns=\"weather\")\n",
+    "\n",
+    "    # Convert 'dt' column from Unix timestamp to datetime and set it as the index\n",
+    "    df['dt'] = pd.to_datetime(df['dt'], unit='s')\n",
+    "    df.set_index('dt', inplace=True)\n",
+    "\n",
+    "    # Display the datafram, with the changes\n",
+    "    display(df)\n",
+    "else:\n",
+    "    print(\"The 'list' key is not present in the JSON file.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Viser temperaturen\n",
+    "Regner ut gjennomsnittst-temperatur ved hjelp av innebygde funksjoner. Finner også høyeste og laveste målte temperatur.\n",
+    "\n",
+    "Plotter temperaturen for perioden."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as mdates\n",
+    "\n",
+    "# Extract main values\n",
+    "temp = df['main.temp']\n",
+    "temp_mean = temp.mean().round(2)\n",
+    "temp_max = temp.max().round(2)\n",
+    "temp_min = temp.min().round(2)\n",
+    "\n",
+    "# Print the average temperature\n",
+    "print(f'Mean temperatur: {temp_mean}')\n",
+    "print(f'Highest temperatur: {temp_max}')\n",
+    "print(f'Lowest temperatur: {temp_min}')\n",
+    "\n",
+    "# Set the x_axis to the index, which means the time\n",
+    "x_axis = df.index\n",
+    "\n",
+    "# Choose the width and height of the plot\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "\n",
+    "# Plotting temperatur\n",
+    "plt.plot(x_axis, temp, color='tab:red', label='Temperatur')\n",
+    "\n",
+    "# Get the current axsis, and store it as ax\n",
+    "ax = plt.gca()\n",
+    "\n",
+    "# Customize the x-axis to show ticks for each hour\n",
+    "ax.xaxis.set_major_locator(mdates.HourLocator(interval=12))  # Tick marks for every hour\n",
+    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%d %b %H'))  # Format as \"Day Month Hour:Minute\"\n",
+    "\n",
+    "# Adjust layout\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Add title for the plot, with city_name and start to end date\n",
+    "plt.title(f'Temperatur {city_name}, from ({start_date}) to ({end_date})')\n",
+    "\n",
+    "# Shows a grid\n",
+    "plt.grid()\n",
+    "\n",
+    "# Show the label-description\n",
+    "plt.legend(loc = 'upper right')\n",
+    "\n",
+    "# Show the plot\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualiserer nedbør\n",
+    "Ved hjelp av matplotlib visualiserer vi nedbør for ønsket periode."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as mdates\n",
+    "import numpy as np\n",
+    "\n",
+    "x_axis = df.index\n",
+    "\n",
+    "# Checks if the rain is a value, it will not be if it is no rain and then cause a KeyError\n",
+    "try:\n",
+    "    rain = df['rain.1h']\n",
+    "\n",
+    "# If no rain, make the rain column and fill it with NaN\n",
+    "except KeyError:\n",
+    "    print(\"'Rain' is not present in the JSON file.\")\n",
+    "    df['rain.1h'] = np.nan\n",
+    "\n",
+    "# Checks if the snow is a value, it will not be if it is no rain and then cause a KeyError\n",
+    "try:\n",
+    "    snow = df['snow.1h']\n",
+    "\n",
+    "# If no snow, make the snow column and fill it with NaN\n",
+    "except KeyError:\n",
+    "    print(\"'Snow' is not present in the JSON file.\")\n",
+    "    df['snow.1h'] = np.nan\n",
+    "\n",
+    "# Choose the width and height of the plot\n",
+    "plt.figure(figsize=(15, 6))\n",
+    "\n",
+    "# Check with rain, will cause NameError if the try/except over fails\n",
+    "try:\n",
+    "    plt.bar(x_axis, rain, width=0.02, alpha=0.5, color='tab:blue', label='rain')\n",
+    "except: NameError\n",
+    "\n",
+    "# Check with snow, will cause NameError if the try/except over fails\n",
+    "try: \n",
+    "    plt.bar(x_axis, snow, width=0.02, alpha=0.5, color='tab:grey', label='snow')\n",
+    "except: NameError\n",
+    "\n",
+    "# Get the current axsis, and store it as ax\n",
+    "ax = plt.gca()\n",
+    "\n",
+    "# Customize the x-axis to show ticks for each hour\n",
+    "ax.xaxis.set_major_locator(mdates.HourLocator(interval=12))  # Tick marks for every hour\n",
+    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%d %b %H'))  # Format as \"Day Month Hour:Minute\"\n",
+    "\n",
+    "# Add the label-desciption\n",
+    "plt.legend(loc = 'upper right')\n",
+    "\n",
+    "# Add title to the plot, with city_name and start to end date\n",
+    "plt.title(f'Precipitation {city_name}, from ({start_date}) to ({end_date})')\n",
+    "\n",
+    "# Shows the plot\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Vise dataframe, med nye kolonner\n",
+    "Hvis dataframen ikke inneholdt 'rain.1h' eller 'snow.1h', skal de nå ha blitt lagt til med 'NaN' verdier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Display df, to see if 'rain.1h' and 'snow.1h' was added with NaN values\n",
+    "display(df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Sjekk for manglende verdier\n",
+    "Missigno sjekker og visualiserer manglende verdier, slik at det blir lettere å se hvilke kolonner feilen ligger i. \n",
+    "\n",
+    "Vis the blir \"hull\" i en søyle, tyder the på manglende verdier."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import missingno as msno\n",
+    "\n",
+    "# Checks for and display missing values\n",
+    "msno.matrix(df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Endre manglende verdier\n",
+    "I de fleste tilfeller virker dataene å være tilnærmet \"perfekte\", men de inkluderer bare snø og regn dersom det er snø eller regn. Derfor vil vi fa NaN verdier i de målingene det ikke har regnet/snødd. \n",
+    "\n",
+    "Under sjekker vi først om regn eller snø er i målingen, og hvis den er, bytter vi ut NaN med 0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# If rain is stored, fill the NaN with 0\n",
+    "try: \n",
+    "    df['rain.1h'] = df['rain.1h'].fillna(0)\n",
+    "except KeyError:\n",
+    "    print([\"'rain.1h', not in df\"])\n",
+    "\n",
+    "# If snow is stored, fill the NaN with 0\n",
+    "try: \n",
+    "    df['snow.1h'] = df['snow.1h'].fillna(0)\n",
+    "except KeyError:\n",
+    "    print(\"['snow.1h'], not in df\")\n",
+    "\n",
+    "# Display the df, now without NaN (atleast for rain and snow)\n",
+    "display(df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualisere endring av data\n",
+    "Har lagt inn en ny missigno visualisering, for å se at de manglende dataene \"forsvinner\" når vi kjører cellen over. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import missingno as msno\n",
+    "\n",
+    "# Visulaize the same data again, but now it should be no missing values (atleast for rain and snow)\n",
+    "msno.matrix(df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualisere data i en graf\n",
+    "Ved hjelp av Matplotlib har vi visualiert ønsket data, og ved hjelp av subplot, en modul i matplotlib, kan vi plotte flere verdier i samme graf, og få \"to y-akse\" på samme x-akse. \n",
+    "\n",
+    "Temperatur og nedbør får plass i samme graf, hvor man leser temperatur verdiene på venstre side, og nedbørsverdiene på høyre side.\n",
+    "\n",
+    "I grafen under, men på samme x-akse, finner vi informasjon om vind, både vindhastighet og vindkast."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.dates as mdates\n",
+    "import os\n",
+    "\n",
+    "# Where the figure should be saved when exported\n",
+    "output_folder = \"../data/output_fig\"\n",
+    "\n",
+    "# Creates the folder if it does not exist\n",
+    "os.makedirs(output_folder, exist_ok=True)\n",
+    "\n",
+    "# x_axis set to the index, which mean the datetime\n",
+    "x_axis = df.index\n",
+    "\n",
+    "# Gets the values\n",
+    "rain = df['rain.1h']\n",
+    "temp = df['main.temp']\n",
+    "snow = df['snow.1h']\n",
+    "wind_gust = df['wind.gust']\n",
+    "wind_speed = df['wind.speed']\n",
+    "\n",
+    "# Two vertically stacked axis, (2 rows, 1 column), width and height of the figure, and the axis share the same x_axis\n",
+    "fig, (ax1, ax3) = plt.subplots(2, 1,figsize=(15, 8), sharex=True)\n",
+    "\n",
+    "\n",
+    "# Set the title for the diagram, above the first axis, with city_name and input_date\n",
+    "ax1.set_title(f'Weather data for {city_name} ({start_date}) to ({end_date}) ')\n",
+    "\n",
+    "# Plot temperature on the primary y-axis\n",
+    "ax1.plot(x_axis, temp, color='tab:red', label='Temperature (°C)')\n",
+    "\n",
+    "# Design the y-axis for temperatur\n",
+    "ax1.set_ylabel('Temperature (°C)', color='tab:red')\n",
+    "ax1.tick_params(axis='y', labelcolor='tab:red')\n",
+    "\n",
+    "# Plot Precipitation as bars on the secondary y-axis\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "# Add rain\n",
+    "ax2.bar(x_axis, rain, color='tab:blue', alpha=0.5, width=0.02, label='Rain (mm)')\n",
+    "\n",
+    "# Add snow\n",
+    "ax2.bar(x_axis, snow, color='tab:grey', alpha=0.5, width=0.02, label='Snow (mm)')\n",
+    "\n",
+    "# Design the y-axis for precipiation\n",
+    "ax2.set_ylabel(\"Precipitation (mm)\", color='tab:blue')\n",
+    "ax2.tick_params(axis='y', labelcolor='tab:blue')\n",
+    "\n",
+    "\n",
+    "# Customize the x-axis to show ticks for each hour\n",
+    "ax1.xaxis.set_major_locator(mdates.HourLocator(interval=12))  # Tick marks for every hour\n",
+    "ax1.xaxis.set_major_formatter(mdates.DateFormatter('%d %b %H'))  # Format as \"Day Month Hour:Minute\"\n",
+    "\n",
+    "# Add label-description for both axis\n",
+    "ax1.legend(loc='upper left')\n",
+    "ax2.legend(loc='upper right')\n",
+    "\n",
+    "# Add grid, but only vertically\n",
+    "ax1.grid(axis = 'x')\n",
+    "\n",
+    "\n",
+    "# Plot the wind at the second x-axis (the axis below)\n",
+    "ax3.plot(x_axis, wind_gust, color='tab:purple', label='Wind_gust')\n",
+    "ax3.plot(x_axis, wind_speed, color='tab:purple', linestyle='dashed', label='Wind_speed')\n",
+    "ax3.set_ylabel('Wind (m/s)')\n",
+    "\n",
+    "# Add x_label visible for both x-axis\n",
+    "ax3.set_xlabel('Datetime')\n",
+    "\n",
+    "# Add label-description\n",
+    "ax3.legend(loc='upper right')\n",
+    "\n",
+    "# Customize the x-axis to show ticks for each hour\n",
+    "ax3.xaxis.set_major_locator(mdates.HourLocator(interval=12))  # Tick marks for every hour\n",
+    "ax3.xaxis.set_major_formatter(mdates.DateFormatter('%d %b %H'))  # Format as \"Day Month Hour:Minute\"\n",
+    "\n",
+    "# Add grid, but only vertically\n",
+    "ax3.grid(axis = 'x')\n",
+    "\n",
+    "# Adjust layout\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Save the plot to the data/output_fig folder\n",
+    "plot_path = os.path.join(output_folder, f\"weather_data_plot{city_name}.png\")\n",
+    "plt.savefig(plot_path)  # Save the plot as a PNG file\n",
+    "\n",
+    "\n",
+    "# Show the plot\n",
+    "plt.show()"
+   ]
+  }
+ ],
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