20210309 - VN_Fuel-Plotly .ipynb

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      "text/html": "        <script type=\"text/javascript\">\n        window.PlotlyConfig = {MathJaxConfig: 'local'};\n        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n        if (typeof require !== 'undefined') {\n        require.undef(\"plotly\");\n        requirejs.config({\n            paths: {\n                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n            }\n        });\n        require(['plotly'], function(Plotly) {\n            window._Plotly = Plotly;\n        });\n        }\n        </script>\n        "
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      "text/html": "        <script type=\"text/javascript\">\n        window.PlotlyConfig = {MathJaxConfig: 'local'};\n        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n        if (typeof require !== 'undefined') {\n        require.undef(\"plotly\");\n        requirejs.config({\n            paths: {\n                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n            }\n        });\n        require(['plotly'], function(Plotly) {\n            window._Plotly = Plotly;\n        });\n        }\n        </script>\n        "
     },
     "metadata": {}
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import datetime\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import matplotlib.dates as mdates\n",
    "import datapane as dp\n",
    "\n",
    "import chart_studio.plotly as py\n",
    "import cufflinks as cf\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# Make Plotly work in your Jupyter Notebook\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "init_notebook_mode(connected=True)\n",
    "# Use Plotly locally\n",
    "cf.go_offline()\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
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       "         Date Regional  RON 95-IV  RON 95-III  E5 RON 92-II  \\\n",
       "55 2019-01-16   Vùng 1      17750       17600         16270   \n",
       "56 2019-01-01   Vùng 1      17750       17600         16270   \n",
       "57 2018-12-21   Vùng 1      18290       18140         16780   \n",
       "58 2018-12-06   Vùng 1      18600       18450         17180   \n",
       "59 2018-11-21   Vùng 1      20120       19970         18620   \n",
       "60 2018-11-06   Vùng 1      21210       21060         19600   \n",
       "61 2018-10-22   Vùng 1      22350       22200         20680   \n",
       "62 2018-10-06   Vùng 1      22490       22340         20900   \n",
       "63 2018-09-21   Vùng 1      21920       21770         20230   \n",
       "64 2018-09-06   Vùng 1      21620       21470         19910   \n",
       "\n",
       "    Diesel Oil 0,001S-V  Diesel Oil 0,05S-II   Period  \n",
       "55                15050                14900   2019-1  \n",
       "56                15050                14900   2019-1  \n",
       "57                16150                16000  2018-12  \n",
       "58                16400                16250  2018-12  \n",
       "59                17780                17630  2018-11  \n",
       "60                18640                18540  2018-11  \n",
       "61                18710                18610  2018-10  \n",
       "62                18710                18610  2018-10  \n",
       "63                18220                18120   2018-9  \n",
       "64                18160                18060   2018-9  "
      ],
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     },
     "metadata": {},
     "execution_count": 115
    }
   ],
   "source": [
    "fuel_df=pd.read_excel(r'https://github.com/ngophuong/DSV_Dataset/blob/main/Vietnam_Fuel_Price.xlsx?raw=true')\n",
    "fuel_df_reg1 = fuel_df[fuel_df['Regional']=='Vùng 1']\n",
    "fuel_df_reg1['Period'] =fuel_df_reg1['Date'].dt.year.astype(str)+str(\"-\")+fuel_df_reg1['Date'].dt.month.astype(str)\n",
    "fuel_df_reg1 = fuel_df_reg1.sort_values(by='Date',ascending= False)\n",
    "fuel_df_reg1 = fuel_df_reg1.reset_index()\n",
    "fuel_df_reg1.drop(fuel_df_reg1.iloc[:,0:2], inplace = True, axis = 1)\n",
    "fuel_df_reg1.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.Markdown object>",
      "text/markdown": "Publishing document and associated data - *please wait...*"
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.Markdown object>",
      "text/markdown": "Your report doesn't contain any text - did you know you can add text to your report once published?"
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.Markdown object>",
      "text/markdown": "Report successfully published at https://datapane.com/u/phuong/reports/diesel-oil-do-vietnam-fuel-price-2019-2021-region-1/ - you can edit and add additional text from the link"
     },
     "metadata": {}
    }
   ],
   "source": [
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=fuel_df_reg1['Date'], y=fuel_df_reg1['Diesel Oil 0,001S-V'],mode='lines+markers',line = dict(color='firebrick', width=3, dash='dash'), name='Diesel Oil DO 0,001S',))\n",
    "\n",
    "fig.add_trace(go.Scatter(x=fuel_df_reg1['Date'], y=fuel_df_reg1['Diesel Oil 0,05S-II'],mode='lines+markers' ,line=dict(color='royalblue', width=3, dash='dot'), name='Diesel Oil 0,05S-II'))\n",
    "\n",
    "#fig.add_trace(go.Scatter(x=fuel_df_reg1['Date'], y=fuel_df_reg1['E5 RON 92-II'], mode='lines', name='E5 RON 92-II', line=dict(width=2, dash='dashdot')))\n",
    "\n",
    "fig.update_layout(title='VN Fuel Price 2019 - 2021 Region 1', font = dict(size = 14),\n",
    "                title_font_color = \"black\",xaxis_title='Year', yaxis_title='Price',height = 800, width = 1800)\n",
    "\n",
    "fig.update_yaxes(automargin=True)\n",
    "\n",
    "fig.update_xaxes(showgrid=False)\n",
    "\n",
    "dp.Report(\n",
    "    dp.Group(\n",
    "        dp.Plot(fig),\n",
    "        dp.Table(fuel_df_reg1)\n",
    "    )\n",
    "        ).publish(name=\"Diesel Oil DO - VietNam Fuel Price 2019-2021 Region 1\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   year       Date Regional   variable  value\n",
       "0  2021 2021-04-27   Vùng 1  RON 95-IV  19260\n",
       "1  2021 2021-04-12   Vùng 1  RON 95-IV  19070\n",
       "2  2021 2021-03-27   Vùng 1  RON 95-IV  19140\n",
       "3  2021 2021-03-12   Vùng 1  RON 95-IV  18980\n",
       "4  2021 2021-02-25   Vùng 1  RON 95-IV  18180"
      ],
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     },
     "metadata": {},
     "execution_count": 59
    }
   ],
   "source": [
    "fuel_df_reg1['year'] = fuel_df_reg1['Date'].dt.year\n",
    "fuel_df_reg1_Boxplot = pd.melt(fuel_df_reg1,id_vars=['year','Date','Regional'],\n",
    "                               value_vars=['RON 95-IV', 'RON 95-III','E5 RON 92-II',\n",
    "                               'Diesel Oil 0,001S-V','Diesel Oil 0,05S-II'])\n",
    "#fuel_df_reg1_Boxplot.dtypes\n",
    "#fuel_df_reg1_Boxplot = fuel_df_reg1_Boxplot[(fuel_df_reg1_Boxplot['year'] < 2021) ]\n",
    "fuel_df_reg1_Boxplot.head()"
   ]
  },
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     },
     "metadata": {}
    }
   ],
   "source": [
    "#Violin Plot for region 1 fuel type\n",
    "fig = go.Figure()\n",
    "px.violin(fuel_df_reg1_Boxplot, x='year', y='value', color = 'variable', \n",
    "          points='all', box = True, title = 'Vietnam Fuel 2018-2021')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "     Unnamed: 0       Date Regional  RON 95-IV  RON 95-III  E5 RON 92-II  \\\n",
       "128         NaN 2018-09-06   Vùng 1      21620       21470         19910   \n",
       "126         NaN 2018-09-21   Vùng 1      21920       21770         20230   \n",
       "124         NaN 2018-10-06   Vùng 1      22490       22340         20900   \n",
       "\n",
       "     Diesel Oil 0,001S-V  Diesel Oil 0,05S-II   Period  year  \n",
       "128                18160                18060   2018-9  2018  \n",
       "126                18220                18120   2018-9  2018  \n",
       "124                18710                18610  2018-10  2018  "
      ],
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     "metadata": {},
     "execution_count": 62
    }
   ],
   "source": [
    "fuel_df_reg1 = fuel_df_reg1.sort_values(by='Date',ascending = True)\n",
    "fuel_df_reg1.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "#only focus on region 1 price data only\n",
    "fuel_df_reg1.dropna(axis = 1, inplace = True)\n",
    "df_2020 = fuel_df_reg1[fuel_df_reg1['year'] == 2020]"
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  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2020[\"DO_Change_pct\"] = df_2020['Diesel Oil 0,05S-II'].pct_change()*100"
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    "df_2020.dropna(axis = 0, inplace = True)"
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   ],
   "source": [
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=df_2020['Date'], y=df_2020['DO_Change_pct'], mode='lines', name='DO 0,05S'))"
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