DemoNotebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eb1bb45c-2d3b-47b5-ad76-5915afa16063",
   "metadata": {},
   "source": [
    "# Description area\n",
    "I can write what I need here\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6c28357f-cb2b-4c15-a61a-6e783911be69",
   "metadata": {},
   "outputs": [],
   "source": [
    "!source venv/bin/activate \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9351e3df-1845-4c4f-bcdf-6b6e40f42d16",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataframe\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>Day</th>\n",
       "      <th>Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000-01-02</td>\n",
       "      <td>22.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>22.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>23.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>21.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-06</td>\n",
       "      <td>20.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>2000-04-06</td>\n",
       "      <td>12.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2000-04-07</td>\n",
       "      <td>10.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>2000-04-08</td>\n",
       "      <td>9.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2000-04-09</td>\n",
       "      <td>10.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2000-04-10</td>\n",
       "      <td>10.28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Day  Temperature\n",
       "0   2000-01-02        22.05\n",
       "1   2000-01-03        22.94\n",
       "2   2000-01-04        23.15\n",
       "3   2000-01-05        21.22\n",
       "4   2000-01-06        20.70\n",
       "..         ...          ...\n",
       "95  2000-04-06        12.64\n",
       "96  2000-04-07        10.84\n",
       "97  2000-04-08         9.04\n",
       "98  2000-04-09        10.10\n",
       "99  2000-04-10        10.28\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pandas import pandas\n",
    "\n",
    "df = pandas.read_csv(\"plot_data.csv\")\n",
    "\n",
    "print(\"Dataframe\")\n",
    "df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03ea977e-5c00-4c90-9d20-136c128a3957",
   "metadata": {},
   "source": [
    "## Line plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "297e485f-5663-4492-961f-b71de76b63cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df.plot(x='Day', y='Temperature', kind='line', marker='o', linestyle='-')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Temperature')\n",
    "plt.title('Line Graph from DataFrame')\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7aac7c3-9b8e-4f7f-ab3e-39179deb9360",
   "metadata": {},
   "source": [
    "## Bar Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6e811d6b-215c-466b-a245-6b593c447256",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(x='Day', y='Temperature', kind='bar', legend=False)\n",
    "plt.locator_params(axis='x', nbins=10) \n",
    "plt.xlabel('Day')\n",
    "plt.ylabel('Temperature')\n",
    "plt.title('Bar Plot from DataFrame')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c8a040a8-7ad2-47a9-9fb0-9b578926a426",
   "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>Day</th>\n",
       "      <th>Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000-01-02</td>\n",
       "      <td>22.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000-01-03</td>\n",
       "      <td>22.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000-01-04</td>\n",
       "      <td>23.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000-01-05</td>\n",
       "      <td>21.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000-01-06</td>\n",
       "      <td>20.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Day  Temperature\n",
       "0  2000-01-02        22.05\n",
       "1  2000-01-03        22.94\n",
       "2  2000-01-04        23.15\n",
       "3  2000-01-05        21.22\n",
       "4  2000-01-06        20.70"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa770fc2-dec0-43ed-8e3c-013ee6ec84e8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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